169 Hypothesis Testing Jobs nearby Mahe

As a Data Scientist, your role will involve designing and implementing workflows for Linear and Logistic Regression, as well as Ensemble Models such as Random Forest and Boosting using R/Python. You should have a strong grasp of Probability and Statistics, with the ability to apply concepts of Data Distributions, Hypothesis Testing, and other Statistical Tests. Experience in handling outliers, denoising data, and managing the impact of unforeseen situations like pandemics is essential. Conducting Exploratory Data Analysis (EDA) on raw data and performing feature engineering when necessary will be part of your responsibilities. Key Responsibilities: - Demonstrating proficiency in Data Visualization using the Python/R Data Science Stack - Leveraging cloud platforms for training and deploying large-scale solutions - Training and evaluating ML models using various machine learning and deep learning algorithms - Ensuring model accuracy is maintained during deployment and retraining as needed - Packaging and deploying large-scale models on on-premise systems using multiple approaches including Docker - Taking complete ownership of the assigned project - Working in Agile environments and utilizing project tracking tools like JIRA - Utilizing cloud platforms such as AWS, Azure, and GCP - Handling NoSQL databases like MongoDB, Cassandra, Cosmos DB, and HBase - Experience in forecasting with products like SAP, Oracle, Power BI, Qlik, etc. - Proficiency in Excel including Power Pivot, Power Query, Macros, and Charts - Working with large datasets and distributed computing tools such as Hive, Hadoop, and Spark - Implementing transfer learning with state-of-the-art models in various domains like vision, NLP, and speech - Integrating with external services and Cloud APIs - Using data annotation approaches and tools for text, images, and videos Qualifications Required: - Strong background in Data Science, Statistics, or related fields - Proficiency in programming languages such as R and Python - Experience with machine learning, deep learning, and statistical modeling - Familiarity with cloud platforms, NoSQL databases, and forecasting tools - Ability to work with large datasets and distributed computing frameworks - Excellent problem-solving skills and the ability to work independently - Strong communication and teamwork skills (Note: Additional details about the company were not provided in the job description.),

As an Analytics Manager at Spinny, you will play a crucial role in fostering a data-first culture and driving data-backed decision-making by collaborating with various teams such as business, product, design, engineering, and growth. Your primary focus will be on leading a team of analysts to extract insights from user behavior, monitor feature performance, and evaluate the impact of products throughout the customer journey. Additionally, you will work closely with senior leadership to tackle complex business challenges using data-driven strategies. **Key Responsibilities:** - Lead a team of analysts to produce high-quality, scalable, and impactful analyses. - Collaborate cross-functionally with marketing, product, sales, and operations teams to define key performance indicators (KPIs), monitor feature usage, and evaluate the effects of product modifications. - Establish and manage scalable dashboards and self-service tools to democratize data accessibility across the organization. - Create and manage frameworks for experimentation and A/B testing to assess business and product initiatives. - Drive data instrumentation initiatives with engineering teams to ensure precise and comprehensive analytics tracking. - Work with the Data Science team on behavioral segmentation, funnel optimization, and personalization strategies. - Mentor junior analysts and cultivate a top-performing analytics team aligned with Spinny's vision. **Requirements:** - 5-8 years of analytics experience, preferably in consumer-tech, e-commerce, or automotive sectors. - Proficiency in SQL, data modeling, Excel, and data visualization tools such as Tableau, Power BI, or Looker. Familiarity with Python/R for data analysis is advantageous. - Understanding of statistics and experimentation methodologies (e.g., A/B testing, hypothesis testing). - Exceptional storytelling and communication skills, with the ability to balance attention to detail and big-picture thinking. - Comfortable operating in dynamic, cross-functional environments. At Spinny, you will have the opportunity to be part of a rapidly growing brand that is revolutionizing the used car industry in India. You will be immersed in a culture that values transparency, ownership, and experimentation, allowing you to solve real customer challenges at scale alongside a dedicated team of professionals.,

As a Manager, Analytics at Expedia Group, you will play a crucial role in leading high-impact analytical projects, delivering actionable insights, and driving data-informed decision-making across the organization. Your responsibilities will include: - Partnering with cross-functional teams to identify key business challenges and provide data-driven insights and recommendations. - Leading the development and delivery of dashboards, reports, and analytical tools to monitor performance and support strategic initiatives. - Conducting in-depth analysis of internal and external data sources to uncover trends, risks, and opportunities. - Translating complex data into clear narratives and visualizations that influence business decisions. - Driving continuous improvement by identifying new data sources, enhancing existing analytics capabilities, and automating manual processes. - Managing relationships with senior stakeholders, ensuring alignment on priorities and delivering high-quality outputs. - Supporting strategic planning, forecasting, and performance reviews with robust analytical input. - Mentoring junior analysts and contributing to a culture of learning and innovation. Qualifications required for this role include: - Bachelors or Masters degree in a quantitative field such as Business, Economics, Statistics, Mathematics, or a related discipline or equivalent experience. - Preferred: 5+ years of experience in analytics, business intelligence, or a related field, with a proven track record of delivering insights that drive business impact. - Proficiency in SQL, Tableau, Excel, and PowerPoint; knowledge of Python or R is a plus. - Strong problem-solving skills and the ability to frame complex business problems as analytical tasks. - Excellent communication and presentation skills, with the ability to influence stakeholders at all levels, including VP+. - Experience managing multiple projects simultaneously and delivering results in a fast-paced environment. - Familiarity with statistical techniques, hypothesis testing, and performance measurement frameworks is a plus. Expedia Group is committed to creating a diverse and inclusive work environment where everyone belongs, differences are celebrated, and success is shared. Join us in shaping the future of travel and be part of a vibrant and welcoming community.,

As a Statistical Analyst at our company, you will play a crucial role in collecting, analyzing, and interpreting data to provide valuable insights for decision-making processes. Your strong background in statistics and data analysis techniques will be essential for this role. **Key Responsibilities:** - Collect, clean, and preprocess data from various sources. - Perform statistical analysis to identify trends, patterns, and relationships in data sets. - Develop predictive models and algorithms for forecasting future trends and outcomes. - Conduct hypothesis testing and interpret results to draw actionable insights. - Collaborate with cross-functional teams to understand business requirements and provide analytical support. - Stay updated on the latest statistical techniques and tools to enhance analytical capabilities. - Assist in designing and implementing experiments to evaluate the effectiveness of business strategies or interventions. **Qualifications:** - Bachelors or Masters degree in Statistics, Mathematics, Economics, Computer Science, or related field. - Proven experience as a Statistical Analyst or in a similar role. - Proficiency in statistical software such as R, Advanced Excel, SAS, or SPSS. - Strong analytical and problem-solving skills with attention to detail. - Excellent communication and interpersonal skills. - Ability to work independently and collaboratively in a fast-paced environment. - Experience with data visualization tools like Tableau or Power BI is a plus. - Knowledge of machine learning techniques and algorithms is desirable. If you are passionate about statistics and enjoy working with complex data sets, we invite you to join our team and contribute to driving data-driven decision-making and strategic initiatives within our organization. This is a full-time, permanent position with a morning shift schedule. One year of work experience is preferred. The work location is in person.,

**Job Description:** **Role Overview:** At Amgen, you will be part of a mission-driven team serving patients living with serious illnesses. As a Sr. Associate V&A Transformation Initiatives, you will play a crucial role in solving key challenges faced by the US Value & Access teams using cutting-edge technology. The focus will be on developing and deploying advanced machine learning, operational research, semantic analysis, and statistical methods to address customer needs and opportunities. **Key Responsibilities:** - Collaborate with the USV&A Transformation team to develop and test AI and advanced statistical solutions for priority business challenges. - Ensure models are trained with the latest data and meet SLA expectations. - Act as a subject matter expert in solving development and commercial questions. - Work with a global cross-functional team on the AI tools roadmap. - Apply technical skills such as hypothesis testing, machine learning, and retrieval processes to identify trends and analyze relevant information. - Perform exploratory and targeted data analyses using descriptive statistics and other methods. - Develop and integrate custom applications, intelligent dashboards, and automated workflows with AI capabilities to enhance decision-making and efficiency. **Qualifications Required:** - **Must-Have Skills:** - Experience with analytic software tools or languages like R and Python. - Strong foundation in machine learning algorithms and techniques. - Experience in statistical techniques, hypothesis testing, regression analysis, clustering, and classification. - **Good-to-Have Skills:** - Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). - Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). - Outstanding analytical and problem-solving skills with the ability to learn quickly. - Experience with data engineering and pipeline development. - Knowledge of NLP techniques for text analysis and sentiment analysis. - Experience in analyzing time-series data for forecasting and trend analysis. - Experience with AWS, Azure, or Google Cloud. - Experience with Databricks platform for data analytics and MLOps. **Additional Details:** Amgen is a collaborative, innovative, and science-based organization with an award-winning culture. As part of the Amgen team, you will have the opportunity to transform the lives of patients while advancing your career. Amgen ensures equal opportunities for individuals with disabilities throughout the job application process, essential job functions, and employment benefits. **Note:** Professional certifications such as AWS Developer certification and Python and ML certification are preferred for this role. **Basic Qualifications:** - Masters degree in computer science, statistics, or STEM majors with a minimum of 2 years of Information Systems experience OR - Bachelors degree in computer science, statistics, or STEM majors with a minimum of 4 years of Information Systems experience.,

As a Modelling Specialist at Standard Chartered, you will be responsible for operational risk capital and stress loss modelling, supporting best practices and methodology, and ensuring regulatory compliance. Your key responsibilities will include driving modelling input into Groups OR ICAAP submission, owning and maintaining capital allocation to business models, and being the subject matter expert for model risk related to all OR models. - Drive the modelling input into Groups OR ICAAP submission - Own and maintain the capital allocation to business models - Be responsible for liaising with group model validation and answer all model related questions - Drive quality input into all relevant internal development and changes in Operational Risk capital - Be the subject matter expert for model risk and provide a point of control over operational risk arising from model risk - Define, formulate, maintain, own, and exercise models for calculating OR capital and stress loss forecasts - Support appropriate governance and routines to align with the Group's mandate Qualifications: - Subject Matter Expert knowledge in operational risk modelling - Understanding of data structures and ability to query data tables - Ability to conduct hypothesis testing and articulate outcomes - Undergraduate and/or postgraduate degree in mathematics, engineering, statistics, data analytics, or any numerate discipline - Previous experience in Operational Risk modelling In addition to the above, if you join Standard Chartered, you will be part of an international bank striving to make a positive difference for clients, communities, and employees. The company values diversity, inclusion, and continuous improvement. Standard Chartered offers various benefits such as retirement savings, medical and life insurance, flexible working options, wellbeing support, continuous learning opportunities, and an inclusive environment where everyone is respected and can realize their full potential.,

As a Data Scientist III, Commercial Operations Analytics at Expedia Group, you will have the opportunity to contribute to enhancing the Account Management space by delivering actionable insights and dashboards. Your role will involve engaging with various stakeholders to identify and prioritize challenges in the lodging area, using your problem-solving skills to frame business challenges as analytical problems, and applying analytics techniques to deliver insights supporting decision-making of account management stakeholders. You will also be responsible for building relationships with different teams across the organization and delivering insights to commercial leaders through clear and compelling storytelling. **Key Responsibilities:** - Engage broadly and proactively with the organization to identify and prioritize challenges arising in the lodging area - Frame business challenges as analytical problems and apply problem-solving techniques to break them down into concrete analytical tasks - Extract data from multiple sources and combine them into the required datasets - Apply analytics techniques to deliver insights supporting decision-making of account management stakeholders - Articulate decision-making rationale, methodology, and recommendations to both technical and non-technical partners through clear and compelling storytelling in presentations **Qualifications Required:** - Bachelors or Masters degree in a quantitative field such as Business, Economics, Statistics, Mathematics, or a related discipline, or equivalent experience - Preferred: 5+ years of experience in analytics, business intelligence, or a related field, with a proven track record of delivering insights that drive business impact - Proficiency in SQL, Tableau, Excel, and PowerPoint; knowledge of Python or R is a plus - Strong problem-solving skills and the ability to frame complex business problems as analytical tasks - Excellent communication and presentation skills, with the ability to influence stakeholders at all levels, including VP+ - Experience managing multiple projects simultaneously and delivering results in a fast-paced environment - Familiarity with statistical techniques, hypothesis testing, and performance measurement frameworks is a plus Expedia Group, known for powering global travel for everyone, offers a diverse, vibrant, and welcoming community where everyone belongs and differences are celebrated. The company values its employees and provides a full benefits package, exciting travel perks, generous time-off, parental leave, a flexible work model, and career development resources to fuel employees" passion for travel and ensure a rewarding career journey.,

Role Overview: As an Assistant Vice President (C12) in the TTS Analytics team at Citi, you will be responsible for leading a team of data scientists and analysts. Your main focus will be on working on various data science projects throughout the year, addressing business problems related to client acquisition, engagement, experience, and retention within the Treasury & Trade Services business. You will need to understand business needs, develop and deploy machine learning models, and effectively communicate insights and recommendations to stakeholders. Your role will involve leveraging different analytical approaches, tools, and techniques to provide data-driven insights and solutions to business and functional stakeholders. Key Responsibilities: - Lead a team of data scientists and analysts responsible for the full lifecycle of machine learning model development and deployment - Work on multiple data science projects addressing business problems across the client life cycle for the TTS business - Understand business needs, design, develop, and deploy machine learning models - Communicate insights and recommendations to stakeholders - Utilize various analytical methods and tools to provide data-driven insights and solutions - Collaborate on projects related to sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention - Build and deploy time series models for forecasting and anomaly detection - Analyze unstructured data using Natural Language Processing (NLP)/Text Mining techniques - Develop end-to-end machine learning pipelines including data preprocessing, feature engineering, model training, evaluation, and deployment Qualifications: - Bachelor's Degree with 7-10 years of experience in data analytics, or Master's Degree with 6-10 years of experience in data analytics, or PhD - Marketing analytics experience - Strong hands-on knowledge of Data Science and Machine Learning - Experience with analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison - Proficiency in Python/R, PySpark, SQL - Familiarity with ML libraries such as Scikit-learn, TensorFlow, and PyTorch - Ability to understand complex business problems and develop analytical approaches to solve them - Excellent logical reasoning and problem-solving skills - Strong communication skills to translate analytical findings into actionable recommendations - Experience in financial services (Good to have) - Deep learning experience with Neural Networks using TensorFlow and/or PyTorch (Good to have) Role Overview: As an Assistant Vice President (C12) in the TTS Analytics team at Citi, you will be responsible for leading a team of data scientists and analysts. Your main focus will be on working on various data science projects throughout the year, addressing business problems related to client acquisition, engagement, experience, and retention within the Treasury & Trade Services business. You will need to understand business needs, develop and deploy machine learning models, and effectively communicate insights and recommendations to stakeholders. Your role will involve leveraging different analytical approaches, tools, and techniques to provide data-driven insights and solutions to business and functional stakeholders. Key Responsibilities: - Lead a team of data scientists and analysts responsible for the full lifecycle of machine learning model development and deployment - Work on multiple data science projects addressing business problems across the client life cycle for the TTS business - Understand business needs, design, develop, and deploy machine learning models - Communicate insights and recommendations to stakeholders - Utilize various analytical methods and tools to provide data-driven insights and solutions - Collaborate on projects related to sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention - Build and deploy time series models for forecasting and anomaly detection - Analyze unstructured data using Natural Language Processing (NLP)/Text Mining techniques - Develop end-to-end machine learning pipelines including data preprocessing, feature engineering, model training, evaluation, and deployment Qualifications: - Bachelor's Degree with 7-10 years of experience in data analytics, or Master's Degree with 6-10 years of experience in data analytics, or PhD - Marketing analytics experience - Strong hands-on knowledge of Data Science and Machine Learning - Experience with analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison - Proficiency in Python/R, PySpark, SQL - Familiarity with ML libraries such as Scikit-learn, TensorFlow, and PyTorch - Ability to understand complex business problems and develop analytical approaches to solve them - Excellent logical reasoning and problem-solving skills - Strong communication skills to translate a

Role Overview: You will be responsible for fetching and transforming data from various systems, conducting in-depth analyses to identify gaps, opportunities, and insights, and providing recommendations that support strategic business decisions. Key Responsibilities: - Data Extraction and Transformation: - Fetch data from multiple systems, transform it to create a unified dataset, and ensure data accuracy. - Data Analysis and Insight Generation: - Analyze large datasets to identify patterns, gaps, and trends. - Develop actionable insights and recommendations that support business objectives. - Visualization and Reporting: - Create impactful visualizations and reports to effectively communicate findings to stakeholders. - Collaboration: - Partner with cross-functional teams to align analytical projects with business goals and translate findings into strategic recommendations. Qualification Required: - Academic Qualifications & Experience Required: - Bachelors or Masters degree in Applied Mathematics, Management Science, Data Science, Statistics, Econometrics, or Engineering. - Extensive experience in Data Lake architecture, building data pipelines using AWS services like EC2, Lambda, Redshift, Glue, Athena, CloudWatch, and S3. - Must be proficient in Python and SQL. - Experience in the banking domain. - High motivation, good work ethic, maturity, and personal initiative. - Strong oral and written communication skills. Additional Details: The company is focused on AI & Data Science Enterprise Delivery and you will be reporting to the VP Business Growth. External stakeholders you will be working with are Clients.,

As a GenAI Data Scientist at PwC US - Acceleration Center, your focus will be on leveraging data to drive insights and make informed business decisions through advanced analytics techniques. You will have the opportunity to optimize client operations and help them achieve strategic goals by utilizing your skills in data manipulation, visualization, and statistical modeling. **Key Responsibilities:** - Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies. - Develop and implement machine learning models and algorithms for GenAI projects. - Perform data cleaning, preprocessing, and feature engineering to prepare data for analysis. - Collaborate with data engineers to ensure efficient data processing and integration into machine learning pipelines. - Validate and evaluate model performance using appropriate metrics and techniques. - Develop and deploy production-ready machine learning applications and solutions. - Utilize object-oriented programming skills to build robust and scalable software components. - Utilize Kubernetes for container orchestration and deployment. - Design and build chatbots using GenAI technologies. - Communicate findings and insights to stakeholders through data visualizations, reports, and presentations. - Stay up-to-date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data science processes. **Qualifications Required:** - 3-5 years of relevant technical/technology experience, with a focus on GenAI projects. - Strong programming skills in languages such as Python, R, or Scala. - Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Experience with data preprocessing, feature engineering, and data wrangling techniques. - Solid understanding of statistical analysis, hypothesis testing, and experimental design. - Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. - Knowledge of data visualization tools and techniques. - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work in a fast-paced and dynamic environment. **Preferred Qualifications:** - Experience with object-oriented programming languages such as Java, C++, or C#. - Experience with developing and deploying machine learning applications in production environments. - Understanding of data privacy and compliance regulations. - Relevant certifications in data science or GenAI technologies. **Nice To Have Skills:** - Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock. - Familiarity with LLM backed agent frameworks such as Autogen, Langchain, Semantic Kernel, etc. - Experience in chatbot design and development. In your role as a GenAI Data Scientist at PwC, you will have the opportunity to apply your expertise in data science and GenAI technologies to drive impactful results for clients. Your advanced analytical skills and knowledge of machine learning will be instrumental in solving complex business problems and delivering innovative solutions.,

As a Data Scientist at EbizON, you will be responsible for analyzing complex datasets, developing data-driven models, and generating actionable insights to support strategic decision-making. You will collaborate with cross-functional teams to design and implement predictive models and machine learning solutions. The ideal candidate for this role is highly analytical, detail-oriented, and passionate about leveraging data to drive innovation and business growth. Key Responsibilities: - Data Modeling & Analysis: Design and develop models to analyze speech, text, and interaction data, including preprocessing pipelines, feature engineering, and outcome evaluation. - Machine Learning Implementation: Build and fine-tune models leveraging LLMs, NLP techniques, ASR/TTS outputs, and structured/unstructured datasets to improve conversational understanding and recommendations. - Experimentation & Evaluation: Design experiments (A/B tests, user behavior analysis), implement evaluation metrics, and continuously iterate on models to improve performance and engagement. - Data Integration: Work with backend teams to integrate ML pipelines into production workflows, APIs, and data stores ensuring robust, scalable data-driven solutions. - Trust, Privacy & Ethics: Collaborate with engineering and compliance teams to ensure data pipelines adhere to privacy laws (PII/PHI), encryption standards, and healthcare guidelines (HIPAA/SOC2). - Collaboration with Cross-Functional Teams: Partner with product, clinical, and engineering teams to translate business requirements into data-driven strategies and actionable insights. - Monitoring & Observability: Implement monitoring, error tracking, and data quality checks for models in production to ensure reliability and fairness. - Accessibility & Fairness: Incorporate accessibility guidelines (ADA/WCAG 2.2), fairness audits, and bias mitigation techniques to ensure inclusive solutions. Required Skills & Experience: - 3 Years Experience in Data Modeling, Machine Learning & AI. - Machine Learning & AI: Hands-on experience with NLP pipelines, LLMs, embeddings, intent classification, speech analytics, or recommendation systems. - Data Engineering: Skilled in building ETL pipelines, data wrangling, feature extraction, and data visualization from large datasets (structured and unstructured). - Statistical Analysis & Experimentation: Experience in hypothesis testing, A/B experiments, causal inference, or clinical outcome analysis. - Programming: Proficiency in Python (Pandas, scikit-learn, TensorFlow/PyTorch), SQL, and APIs for data integration. - Cloud Infrastructure: Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker), data lakes, and distributed computing frameworks. - Security & Privacy: Understanding of data encryption, secure storage, and compliance frameworks related to PHI/PII. - Healthcare Domain Knowledge: Experience with healthcare datasets, patient data, or compliance requirements like HIPAA or SOC2 is preferred. - Communication & Collaboration: Ability to explain data-driven insights clearly to non-technical stakeholders, work across product, engineering, and clinical teams. - Problem Solving & Curiosity: Strong analytical mindset with a passion for deriving insights from complex data and designing models that drive user experience improvements. About Us: EbizON is an international team specializing in building technology products and helping brands grow with multi-channel demand generation marketing. The company values integrity, creativity, innovation, mindfulness, and teamwork. EbizON provides equal opportunities for all employees and believes in flexible working hours to help employees thrive and maintain a work-life balance. The company also offers global client exposure and organizes retreats, town halls, and festive celebrations to foster a fun and friendly work culture.,

As a Data Scientist with 4-6 years of experience, you will be responsible for leveraging Machine Learning and Statistical Analysis to derive actionable insights and drive data-led decision-making for real-world business problems. Key Responsibilities: - Design, implement, and apply Machine Learning techniques to address business challenges effectively. - Conduct statistical analysis to validate hypotheses and interpret patterns within large datasets. - Perform qualitative analysis to extract insights from non-numerical data sources. - Collaborate closely with cross-functional teams to define data-driven solutions. - Clearly communicate findings through dashboards, reports, and presentations. Required Skills: - Strong understanding of Machine Learning algorithms with a focus on practical implementation. - Hands-on experience with Python, Pandas, Scikit-learn, TensorFlow, or PyTorch. - Solid foundation in Statistics including hypothesis testing, regression, sampling, and data modeling. - Exposure to Qualitative Data Analysis methods and frameworks. - Excellent analytical, problem-solving, and storytelling skills. In addition, the company offers a happy workplace with a fun, inclusive, and collaborative work environment, prioritizes health with medical insurance for you and your family, 1:1 mental wellness sessions, and wellness initiatives. You will have access to Indium Academy, the internal learning platform for continuous upskilling, and support for maintaining work-life balance through a flexible hybrid work model and various destressing and employee engagement activities.,

As an IT Data Engineer at Qualcomm India Private Limited, you will play a crucial role in handling and analyzing large datasets. Your responsibilities will include: - Writing efficient SQL queries, solving real-world case studies, and practicing advanced topics like window functions and CTEs. - Demonstrating proficiency in Python basics for data cleaning with Pandas and NumPy, along with experience in automation. - Utilizing BI tools such as Tableau, Power BI, or Splunk to present actionable insights, build dashboards, create data models, and develop visually engaging reports and alerts with data refresh schedules. - Understanding statistical concepts like mean, median, mode, standard deviation, hypothesis testing, confidence intervals, and basics of probability. Qualcomm values candidates with the following qualifications: - Minimum of 4 years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or a related field, or 6+ years of IT-related work experience without a Bachelor's degree. - At least 2 years of work experience in programming (e.g., Java, Python), 1+ year of work experience with SQL or NoSQL databases, and 1+ year of work experience with data structures and algorithms. - Bachelors/Masters or equivalent degree in computer engineering or a related field. Additionally, any certification in the mentioned skills would be an added advantage. Qualcomm is an equal opportunity employer committed to providing accessible and reasonable accommodations for individuals with disabilities during the application and hiring process. The company expects its employees to adhere to all policies and procedures, including security measures for protecting confidential information. Please note that our Careers Site is exclusively for individuals seeking job opportunities at Qualcomm, and unsolicited resumes or applications from staffing and recruiting agencies will not be accepted. For more information about this role, please reach out to Qualcomm Careers.,

As an AI/Data Science Senior Analyst at Accenture Marketing + Communications Data & Analytics team, your role is crucial in delivering high-value insights and analytics capabilities to empower Marketing + Communications through data-driven strategies. You will be responsible for ideating and developing innovative data science and AI solutions to provide actionable recommendations for clients, talent, and internal marketing teams. Collaboration with senior marketing stakeholders to understand business needs and leading teams of data scientists and engineers will be key to delivering high-quality solutions. **Key Responsibilities:** - Drive the development and execution of data-driven strategies to contribute to the organization's overall goals and business objectives. - Develop and implement AI/ML models to deliver data-driven insights and innovative solutions for business stakeholders. - Translate data-driven findings into clear and concise recommendations for technical and non-technical audiences, enabling strategic decision-making based on insights. - Analyze structured and unstructured data using advanced analytics and NLP techniques, visualizing findings intuitively. - Ensure data quality, integrity, and privacy by implementing best practices for data collection, processing, and storage. - Foster a collaborative work environment that encourages knowledge sharing and cross-team collaboration. - Write clean, modular, and well-documented Python code for model development and automation. - Support the integration of ML models into production using established MLOps practices and pipelines. - Stay updated with the latest trends in AI/ML, particularly in areas like LLM fine-tuning, FastAPI, and agent-based systems. **Qualifications Required:** - Education: Bachelor's or master's degree in a quantitative discipline (Computer Science, Statistics, Data Science, Engineering, or related field). - Work Experience: 2+ years of hands-on experience in applied machine learning or data science roles, with a preference for B2B marketing analytics experience. - Core Skills: Strong programming skills in Python with proficiency in libraries like Pandas, Scikit-learn, and NumPy. Solid understanding of statistical modeling, hypothesis testing, and evaluation metrics. Experience with classical machine learning techniques, model deployment, MLOps workflows, SQL, and digital marketing data sources and technologies. - Nice to Have Skills: Exposure to FastAPI, LLM fine-tuning, agentic AI, cloud platforms (GCP, AWS, Azure), and tools like Snowflake, BigQuery. - Other Requirements: Excellent communication, presentation, critical thinking, collaboration, attention to detail, project management, and relationship-building skills. Ability to influence leadership, prioritize projects, and operate with high energy and enthusiasm in a fast-paced environment. This role offers you the opportunity to be at the forefront of developing cutting-edge data science and AI solutions while collaborating with a diverse team to drive impactful results in a dynamic and challenging setting.,

As a Senior Data Science Lead, your primary skills should include: - Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic) - Proficiency in Python/PySpark, SAS/SPSS - Statistical analysis and computing - Familiarity with Probabilistic Graph Models, Great Expectation, Evidently AI - Experience in Forecasting (Exponential Smoothing, ARIMA, ARIMAX) - Knowledge of Tools like KubeFlow, BentoML - Expertise in Classification (Decision Trees, SVM) - Familiarity with ML Frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet - Understanding of Distance metrics like Hamming Distance, Euclidean Distance, Manhattan Distance - Knowledge of R/ R Studio In this role as the Agentic AI Lead, you will be responsible for driving the research, development, and deployment of semi-autonomous AI agents to tackle complex enterprise challenges. Your key responsibilities will include: - Architecting & Scaling Agentic AI Solutions: - Designing and developing multi-agent AI systems using LangGraph for workflow automation - Building memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains - Defining and implementing scalable architectures for LLM-powered agents that integrate with enterprise applications - Hands-On Development & Optimization: - Developing and optimizing agent orchestration workflows using LangGraph - Implementing knowledge graphs, vector databases, and retrieval-augmented generation techniques - Applying reinforcement learning methodologies to fine-tune AI agents for improved decision-making - Driving AI Innovation & Research: - Leading cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents - Staying ahead of advancements in multi-agent systems and AI planning - Prototyping and experimenting with self-learning AI agents for autonomous adaptation - AI Strategy & Business Impact: - Translating Agentic AI capabilities into enterprise solutions for automation and cost savings - Leading Agentic AI proof-of-concept projects that demonstrate tangible business impact - Mentorship & Capability Building: - Leading and mentoring a team of AI Engineers and Data Scientists - Establishing best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents Overall, you will play a pivotal role in the development and implementation of advanced AI solutions that drive business impact and innovation within the organization.,

As an Associate Data Scientist, Digital & Transformation, you will play a crucial role in supporting a multidisciplinary team by designing and developing innovative data-driven analytical products and solutions. Your responsibilities will include applying advanced analytics, data mining, machine learning, and emerging Generative AI techniques to tackle strategic business challenges and drive measurable outcomes. Key Responsibilities: - Apply statistical, machine learning, and Generative AI techniques to address strategic business problems. - Retrieve, clean, and prepare structured, semi-structured, and unstructured data from diverse sources. - Support exploratory analysis, algorithm design, model development, and advanced analytics under guidance. - Contribute to building scalable, automated processes for data analysis, model validation, and deployment. - Assist in developing tools to monitor and evaluate model performance, accuracy, and fairness. - Create data-driven insights, dashboards, and visualizations for stakeholder communication. - Collaborate with internal experts and cross-functional teams to operationalize AI solutions. - Participate in research and prototyping with agentic AI frameworks (e.g., LangGraph, OpenAI Agents). Qualifications Required: - Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science, or another quantitative discipline with a strong academic record. - Minimum 1-3 years of related work experience. - Proficiency in Python for data manipulation, scripting, prototyping, and familiarity with AI-assisted coding. - Foundational to advanced experience with machine learning technologies and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). - Exposure to agentic AI frameworks (e.g., LangGraph, OpenAI Agents) and familiarity with agent patterns and their effective applications. - Solid understanding of AI system development, validation, and evaluation practices. - Experience with Jupyter notebooks, Anaconda environments, or similar tools for experimentation and workflow management. - Strong grasp of statistics and data science methods (e.g., regression, hypothesis testing, probability distributions). - Basic to intermediate knowledge of distributed systems, scalable computing approaches, and containerization (e.g., Docker). - Exposure to cloud platforms (Azure, AWS) and related AI services such as Azure ML, Azure AI Foundry/OpenAI platform, Azure Cognitive Services, and AI Search. - Familiarity with web services, microservices, and REST APIs, as well as building and working with data architectures. - Basic knowledge of BI/visualization tools (e.g., Power BI, Microsoft Fabric). - Understanding of modern computer vision techniques. - Product development mindset with the ability to work in fast-paced, agile environments. - Independent and creative approach to problem-solving with the ability to prioritize effectively and deliver with urgency. - Strong communication and collaboration skills in global and virtual team settings. Please note the willingness to work in the 12:00 PM - 9:00 PM shift for global collaboration support.,

Role Overview: As a Data Scientist at WAC, you will play a crucial role in transforming complex data into actionable insights that drive business strategies and foster innovation. Your primary responsibility will involve collaborating with cross-functional teams to develop and implement data science solutions that align with the organization's business objectives. Key Responsibilities: - Data Exploration: Gather, clean, and preprocess data from diverse sources to uphold data quality and integrity. - Statistical Analysis: Utilize advanced statistical and machine learning techniques to analyze data and derive valuable insights. - Model Development: Create, refine, and optimize predictive and machine learning models tailored to address specific business challenges and opportunities. - Data Visualization: Develop visually appealing reports and dashboards to effectively present data findings to both technical and non-technical stakeholders. - Hypothesis Testing: Formulate and validate hypotheses to confirm assumptions and offer data-driven recommendations. - Feature Engineering: Identify and engineer pertinent features to enhance model performance and accuracy. - A/B Testing: Plan and execute experiments to assess the impact of modifications and optimizations. - Data Storytelling: Articulate complex technical findings in a clear and understandable manner to aid decision-makers. - Collaboration: Engage with teams throughout the organization to comprehend business goals and deliver data-driven insights and recommendations. - Continuous Learning: Keep abreast of the latest advancements in data science, machine learning, and analytics to leverage cutting-edge techniques and tools. Qualifications Required: - Master's or Ph.D. degree in a relevant field like Data Science, Statistics, Computer Science, or related disciplines. - Minimum of 4 years of experience as a Data Scientist or in a similar capacity. - Proficiency in data analysis tools and languages, such as Python or R. - Strong understanding of machine learning techniques and libraries. - Familiarity with data visualization tools such as Tableau, Power BI, or equivalent. - Exceptional problem-solving abilities and a knack for critical and analytical thinking. - Effective communication and storytelling skills, enabling you to elucidate complex technical concepts to non-technical audiences. - Knowledge of data ethics and the ethical utilization of data. Note: The JD did not include any additional details about the company.,

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Responsibilities: - Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies. - Develop and implement machine learning models and algorithms for GenAI projects. - Perform data cleaning, preprocessing, and feature engineering to prepare data for analysis. - Collaborate with data engineers to ensure efficient data processing and integration into machine learning pipelines. - Validate and evaluate model performance using appropriate metrics and techniques. - Develop and deploy production-ready machine learning applications and solutions. - Utilize object-oriented programming skills to build robust and scalable software components. - Utilize Kubernetes for container orchestration and deployment. - Design and build chatbots using GenAI technologies. - Communicate findings and insights to stakeholders through data visualizations, reports, and presentations. - Stay up-to-date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data science processes. Requirements: - 3-5 years of relevant technical/technology experience, with a focus on GenAI projects. - Strong programming skills in languages such as Python, R, or Scala. - Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Experience with data preprocessing, feature engineering, and data wrangling techniques. - Solid understanding of statistical analysis, hypothesis testing, and experimental design. - Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. - Knowledge of data visualization tools and techniques. - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work in a fast-paced and dynamic environment. Preferred Qualifications: - Experience with object-oriented programming languages such as Java, C++, or C#. - Experience with developing and deploying machine learning applications in production environments. - Understanding of data privacy and compliance regulations. - Relevant certifications in data science or GenAI technologies. Nice To Have Skills: - Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock. - Familiarity with LLM backed agent frameworks such as Autogen, Langchain, Semantic Kernel, etc. - Experience in chatbot design and development. Professional And Educational Background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA,

Role Overview: As an Analyst at Tesco, your primary responsibility will be to analyze complex datasets and present them in a consumable format using visual storytelling and visualization tools such as reports and dashboards, specifically utilizing tools like Tableau and PyDash. Key Responsibilities: - Follow the Business Code of Conduct diligently, always act with integrity, and take on specific risk responsibilities. - Identify operational improvements and implement solutions using Continuous Improvement (CI) tools and techniques. - Complete tasks and transactions within agreed Key Performance Indicators (KPIs). - Engage with market partners to understand business problems, translate them into analytical problems, and provide insights to decision-makers. - Manipulate, analyze, and synthesize large complex datasets from various sources while ensuring data quality and integrity. - Ensure high-quality and timely completion of work deliverables. - Support automation of repeatable tasks, report generation, or dashboard refresh. - Develop in-depth analysis and reports that go beyond basic requirements. - Write well-detailed, structured, and efficient codes. - Contribute to the development of knowledge assets and reusable modules. - Generate practical insights to drive business decisions. - Understand business needs and Tesco processes thoroughly. Qualifications Required: - Basic understanding of Business Decisions. - Skills to develop visualizations, self-service dashboards, and reports using Tableau. - Basic Statistical Concepts knowledge including Correlation Analysis and Hypothesis Testing. - Ability to analyze data using Advanced Excel, SQL, Hive, and Basic Data Warehousing concepts on Hadoop and Teradata. - Automation skills using Alteryx/Python are considered advantageous. - 1-2 years of experience in analytics delivery in domains like retail, CPG, telecom, or hospitality, preferably in functional areas like marketing, supply chain, customer, merchandising, operations, finance, or digital. About the Company: At Tesco, inclusion is a core value that drives everything they do. They believe in treating everyone fairly and with respect, creating a sense of belonging and valuing individuality. Diversity and inclusion are deeply embedded in their culture, fostering an inclusive workplace where all colleagues can thrive and contribute to the success of the business. Tesco Bengaluru is committed to offering equal opportunities to all candidates, including those with disabilities, and provides a supportive environment for individuals with disabilities. Their recruitment process is fully accessible, and they offer reasonable adjustments during interviews to ensure everyone has the chance to succeed. Moreover, Tesco promotes a work environment that allows for professional and personal growth, offering a hybrid work model that combines in-person collaboration with remote work to accommodate the unique life journeys of their employees.,

As a Data Scientist at Maruti Suzuki's Analytics Centre of Excellence (ACE) CoE, your role will involve the following key responsibilities: - Designing and implementing workflows for Linear and Logistic Regression, as well as Ensemble Models (Random Forest, Boosting) using R/Python. - Demonstrating competency in Probability and Statistics, including utilizing concepts of Data Distributions, Hypothesis Testing, and other Statistical Tests. - Experience in handling outliers, denoising data, and managing the impact of pandemic-like situations. - Performing Exploratory Data Analysis (EDA) of raw data and conducting feature engineering where applicable. - Proficiency in Data Visualization using the Python/R Data Science Stack. - Leveraging cloud platforms for training and deploying large-scale solutions. - Training and evaluating ML models using various machine learning and deep learning algorithms. - Retraining and maintaining model accuracy in deployment. - Packaging and deploying large-scale models on on-premise systems using multiple approaches, including docker. - Taking complete ownership of the assigned project. - Experience of working in Agile environments. - Familiarity with JIRA or equivalent project tracking tool. In terms of competencies and skills, you should have knowledge of cloud platforms such as AWS, Azure, and GCP. Exposure to NoSQL databases like MongoDB, Cassandra, Cosmos DB, HBase is preferred. Forecasting experience in products like SAP, Oracle, Power BI, Qlik, etc. is beneficial. Proficiency in Excel, including Power Pivot, Power Query, Macros, and Charts, is required. Experience with large datasets and distributed computing (Hive/Hadoop/Spark) is a plus. Additionally, familiarity with transfer learning using state-of-the-art models in various domains like vision, NLP, and speech, integration with external services and Cloud API, working with data annotation approaches and tools for text, images, and videos is desirable. Your work experience should range from a minimum of 2 years to a maximum of 8 years, and you should hold a Bachelor of Technology (B.Tech) or equivalent educational qualification.,