1 Senior Data Scientist Jobs nearby Manesar

We are looking for a detail-oriented tax associate to consult with clients and provide tax preparation services. The tax associate will report to a senior tax professional. The tax associate's responsibilities include interacting with clients, obtaining and reviewing tax information, preparing tax returns, and performing tax research projects. To be successful as a tax associate you should be able to ensure your clients comply with IRS regulations and work to minimize their tax liabilities. Tax Associate Responsibilities: Ensuring clients comply with IRS regulations and meet their state and federal tax obligations. Analyzing and minimizing tax liabilities by implementing tax reduction strategies. Reviewing financial records, income statements, and expenditures. Preparing and filing tax returns and work papers for companies, partnerships, and individuals. Researching tax issues and assisting with tax audits. Consulting with clients, reviewing their tax information, and responding to questions and concerns. Advising clients on employee health care benefits, compensation, and accounting systems. Maintaining accurate and up-to-date client records. Tax Associate Requirements: Degree in taxation or accounting required. CPA certification may be required. 1+ years of tax preparation experience. Experience using tax preparation software and applications. Good communication skills, both verbal and written. Ability to prioritize and manage time efficiently. Strong analytical and problem-solving skills. Excellent accounting skills. Good customer service skills.

Job Title Manager / Sr. Manager Hydraulics (Steel Melt Shop) Position Overview As the Hydraulics Manager for the Steel Melt Shop, you will be responsible for overseeing and managing hydraulic systems and operations across critical plant equipment including arc furnaces, induction furnaces, casting lines (slab & bloom casters), auto-grinders, bailing presses, and related machinery. You will ensure optimal performance, reliability, and safety of hydraulic systems, coordinate maintenance and repairs, and lead a team to support continuous production operations. Key Responsibilities Oversee day-to-day hydraulic operations for the melt shop ensure all hydraulic systems (furnaces, casters, presses, grinders, etc.) are functioning optimally. Plan, schedule, and supervise preventive, predictive, and corrective maintenance of hydraulic systems; ensure timely repairs to minimize downtime and maximize equipment availability. Perform routine inspections and diagnostics of hydraulic components monitor hydraulic fluid levels, detect leaks, check pumps/valves/cylinders/pipelines, replace seals/filters/hoses as required. Manage spare parts inventory and critical hydraulic components ensure availability of spares and consumables to support continuous maintenance and operations. Coordinate maintenance activities with production and other departments to plan shutdowns or maintenance windows without disrupting production flow. Lead, mentor, and manage a team of hydraulic technicians, fitters, and maintenance staff assign tasks, monitor performance, provide training, and ensure adherence to safety and operational standards. Monitor key performance indicators (KPIs) related to hydraulic systems: uptime, mean time between failures (MTBF), maintenance costs, breakdown frequency, repair turnaround time analyze data and drive continuous improvements. Implement and enforce safety protocols, plant safety standards, and regulatory compliance in all hydraulic maintenance and operations activities. Participate in audits, inspections, and process reviews related to hydraulic systems and maintenance procedures; maintain accurate maintenance logs, records, and documentation. Support commissioning, upgrades, or installation of new hydraulic equipment or systems coordinate testing, integration, and validation of new setups. Collaborate with engineering, production, maintenance planning, and safety teams for seamless hydraulic operations and alignment with overall plant objectives. Respond promptly to breakdowns or emergencies, organize troubleshooting and repairs, and take corrective actions to restore operations with minimal downtime.  

Role Overview: As an Analytics Engineer at MongoDB, you will play a critical role in leveraging data to drive informed decision-making and simplify end user engagement across our most critical data sets. You will be responsible for designing, developing, and maintaining robust analytics solutions, ensuring data integrity, and enabling data-driven insights across all of MongoDB. This role requires an analytical thinker with strong technical expertise to contribute to the growth and success of the entire business. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities: - Design, implement, and maintain highly performant data post-processing pipelines - Create shared data assets that will act as the company's source-of-truth for critical business metrics - Partner with analytics stakeholders to curate analysis-ready datasets and augment the generation of actionable insights - Partner with data engineering to expose governed datasets to the rest of the organization - Make impactful contributions to our analytics infrastructure, systems, and tools - Create and manage documentation, and conduct knowledge sharing sessions to proliferate tribal knowledge and best practices - Maintain consistent planning and tracking of work in JIRA tickets Qualification Required: - Bachelors degree (or equivalent) in mathematics, computer science, information technology, engineering, or related discipline - 2-4 years of relevant experience - Strong Proficiency in SQL and experience working with relational databases - Solid understanding of data modeling and ETL processes - Proficiency in Python for data manipulation and analysis - Familiarity with CI/CD concepts and experience with managing codebases with git - Experience managing ETL and data pipeline orchestration with dbt and Airflow - Familiarity with basic command line functions - Experience translating project requirements into a set of technical sub-tasks that build towards a final deliverable - Committed to continuous improvement, with a passion for building processes/tools to make everyone more efficient - The ability to effectively collaborate cross-functionally to drive actionable and measurable results - A passion for AI as an enhancing tool to improve workflows, increase productivity, and generate smarter outcomes - Strong communication skills to document technical processes clearly and lead knowledge-sharing efforts across teams - A desire to constantly learn and improve themselves Additional Company Details: MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. MongoDB is an equal opportunities employer.,

As a motivated and highly skilled Data Scientist joining the Flight Safety team, your role will be crucial in utilizing advanced analytics and machine learning techniques to drive safety-related decisions and enhance operational processes. You will primarily focus on analyzing time-series and multivariate data to detect anomalies, identify patterns, and create predictive models that contribute to improving flight safety and minimizing risks. - Conduct exploratory data analysis to reveal insights from complex datasets - Apply advanced anomaly detection techniques to spot irregularities and potential safety risks - Develop machine learning and deep learning models like ANN, RNN, and CNN for predictive safety analytics - Support data-driven decision-making within the field of flight safety using big data analytics tools and AI/ML frameworks - Design custom algorithms tailored to meet specific domain requirements with precision and reliability - Write efficient, maintainable code in Python and MATLAB for data processing, modeling, and algorithm deployment - Collaborate with cross-functional teams to translate analytical findings into actionable safety initiatives To qualify for this role, you should: - Hold a Bachelor's degree in Engineering with a specialization in Data Science or a related field - Have certification in Data Science - Possess a minimum of 6 years of practical experience in data science, machine learning, or analytics roles - Have a proven track record in developing AI/ML models, particularly in anomaly detection and predictive analytics - Demonstrate proficiency in data analysis, exploratory data analysis, anomaly detection (time-series & multivariate data), machine learning, deep learning, big data analytics, and AI-driven risk forecasting - Showcase strong programming skills in Python and MATLAB - Exhibit expertise in custom algorithm design, data collection, preprocessing, and integration By joining the team, you will have the opportunity to contribute to cutting-edge data science projects in the aviation safety sector, work in a collaborative and innovation-oriented environment, and be part of a mission-critical team dedicated to predictive safety and operational excellence. (Note: The additional details of the company were not present in the provided job description),

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 a Senior Data Scientist at AuxoAI, you will be responsible for designing, deploying, and scaling production-grade ML systems. Your expertise in AI, machine learning engineering (MLE), and generative AI will be crucial in this role. You will have the opportunity to work on large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This position is perfect for someone who enjoys combining cutting-edge research with production rigor and is passionate about mentoring while creating impactful AI applications. Your key responsibilities will include: - Owning the full ML lifecycle: from model design to training, evaluation, and deployment - Designing production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection - Fine-tuning LLMs and implementing retrieval-augmented generation (RAG) pipelines - Building agentic workflows for reasoning, planning, and decision-making - Developing real-time and batch inference systems using Docker, Kubernetes, and Spark - Leveraging state-of-the-art architectures like transformers, diffusion models, RLHF, and multimodal pipelines - Collaborating with product and engineering teams to integrate AI models into business applications - Mentoring junior team members and promoting MLOps, scalable architecture, and responsible AI best practices Qualifications required for this role: - 6+ years of experience in designing, deploying, and scaling ML/DL systems in production - Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX - Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines - Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration) - Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows - Strong software engineering background with experience in testing, version control, and APIs - Proven ability to balance innovation with scalable deployment - B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field If you have open-source contributions, GenAI research experience, or have worked on applied systems at scale, it would be considered a bonus.,

Role Overview: As a Senior Manager - Credit Portfolio & Data Analytics in the Post Acquisition sub vertical of Credit & Fraud Risk Management function located in Gurugram, your role is crucial for implementing strategies and policies to drive portfolio growth, maintain delinquencies within benchmarks, and launch campaigns to achieve organizational goals effectively. Key Responsibilities: - Maintain & sustain profitability in Encash Portfolio and keep delinquency rates below benchmark levels - Offer encash & CLI to low and marginal Risk segments, acting as an NEA builder for the portfolio - Utilize data from other bureaus effectively to offer encash to customers - Track & monitor portfolio performance, taking corrective actions to maintain delinquency within benchmark rates - Identify opportunity or stress segments in the portfolio and take appropriate actions - Conduct data analytics, modelling, and segmentation for portfolio management - Optimize x-sell coverage of the portfolio by culling out segments - Promote customer-driven actions such as increase income-driven limit assignment - Create and monitor the portfolio Performance dashboard on time monthly - Review transaction declines daily, highlighting gaps and abnormal patterns - Support the implementation of regulatory guidelines and network enhancements - Drive portfolio management initiatives by collaborating with marketing, IT, operations, and collection teams - Implement AI /ML /Automation techniques in business processes for enhanced efficiency and customer experience - Manage the exit process of all secured cards with partner banks Qualifications Required: - Expertise in Data Analytics & Modelling - Strong understanding of cards business dynamics - Proficiency in data analytics and system tools such as SAS, TRIAD, V+, Python Additional Details: The company operates in the Financial Services Industry and values competencies critical for this role, including Stakeholder Management, Written and Verbal Communication, Analytical Skills & Problem Solving, Process Orientation, Agility & Responsiveness. You will collaborate with key external stakeholders like Credit Bureaus, Card Networks, Vendors and internal stakeholders across all functions. A Masters degree in economics, statistics, or business management along with 6-8 years of post-qualification experience is required for this role.,

As a member of the Data & Analytics team in Financial Services Consulting at EY, your role will involve performing business and technical analysis of current systems, gathering and documenting requirements for new solutions, facilitating workshops with stakeholders, and translating requirements into user stories and process flows. You will work closely with Technical and Solution Architects to ensure design standards are met and collaborate with the project team to ensure full test coverage. Your responsibilities will also include data profiling, data analysis, and preparing data reports and visualizations for stakeholders. Key Responsibilities: - Perform business and technical analysis of current systems - Gather and document business and technical requirements for new solutions - Facilitate workshops with multiple stakeholders - Translate functional and non-functional requirements into accurate user stories and process flows - Conduct stakeholder interviews - Ensure traceability of requirements from design to solution - Work with the project team to ensure full test coverage of all requirements - Present data using graphs, charts, tables, etc. - Prepare concise data reports and visualizations for stakeholders Skills and attributes for success: - Solid experience in querying and analyzing data using SQL - Experience working in multi-disciplinary teams - Demonstrated experience in documenting requirements Qualifications: - Minimum 3 years of experience in the Financial Services industry - Academic background in Data & Analytics, Engineering, IT, Business, Economics, Finance, or Accounting - Consulting skills and knowledge of Aladdin Blackrock, eFront, SimCorp Dimension, Temenos WealthSuite, and Avaloq platforms - Ability to work with senior stakeholders and adapt to demanding environments Additional Company Details: EY is dedicated to building a better working world by creating long-term value for clients, people, and society, and fostering trust in the capital markets. With diverse teams in over 150 countries, EY provides trust through assurance and helps clients grow, transform, and operate across various service areas. EY values continuous learning, transformative leadership, and a diverse and inclusive culture. If you meet the criteria and are a highly motivated individual with excellent problem-solving skills, effective communication abilities, and a desire to develop your career in a dynamic organization, we encourage you to apply to join us in shaping a better working world at EY. Apply now to be a part of EY's mission to shape the future with confidence.,

As a member of the Analytics, Investment Optimization and Marketing Enablement (AIM) team at American Express, your role will involve spearheading analytics to drive beyond the card strategies comprising cross-sell and engagement. You will be responsible for driving multiple US SME strategic growth priorities like BLOC, BCA, Blueprint, and AP Automation. Your key responsibilities include supporting and enabling the GCS product partners with actionable, insightful analytical solutions to help the leadership team evaluate and drive business performance. You will also partner with functional leaders, Strategic Business Partners, and Senior leaders to assess and identify opportunities for better customer engagement and revenue growth. Your excellent communication skills will be essential in engaging, influencing, and inspiring partners and stakeholders to drive collaboration and alignment. Additionally, you will need exceptional execution skills to resolve issues, identify opportunities, define success metrics, and drive automation and ongoing refinement of analytical frameworks. Your willingness to challenge the status quo and engage in breakthrough thinking to generate insights, alternatives, and opportunities for business success will be crucial. Qualifications required for this role: - Degree in a quantitative field (e.g. Finance, Engineering, Mathematics, Computer Science, or Economics). - Strong technical and analytical skills with the ability to apply quantitative methods and business skills to create insights and drive results. - Ability to work independently and across a matrix organization, partnering with business partners, functional owners, capabilities, technology teams, and external vendors. - Strong programming skills are preferred, and experience with Big Data programming is a plus. - Ability to prioritize and manage several concurrent projects through collaboration across teams and geographies. American Express supports your holistic well-being by offering: - Competitive base salaries and bonus incentives - Support for financial well-being and retirement - Comprehensive medical, dental, vision, life insurance, and disability benefits - Flexible working model with hybrid, onsite, or virtual arrangements depending on role and business need - Generous paid parental leave policies - Free access to global on-site wellness centers staffed with nurses and doctors - Free and confidential counseling support through the Healthy Minds program - Career development and training opportunities Please note that an offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.,

As a highly skilled Data Business Analyst, your role will involve working closely with business stakeholders, data engineers, and product teams to translate business requirements into effective data solutions. It is essential to have expertise in SQL, Data Warehousing concepts, ETL processes, Data Modeling, and Data Mapping. Experience with cloud-based data platforms is an added advantage. **Key Responsibilities:** - Collaborate with business stakeholders to gather, analyze, and document data requirements - Translate business needs into functional specifications, data models, and process flows - Perform deep-dive data analysis using advanced SQL queries - Work with ETL and data engineering teams to ensure accurate data pipelines and transformations - Support Data Warehousing initiatives, including data modeling (conceptual, logical, and physical) - Develop and maintain data mapping documents and source-to-target (S2T) specifications - Perform data validation, profiling, and quality checks to ensure data accuracy - Assist in defining KPIs, building dashboards, and supporting reporting needs - Communicate findings and insights to technical and non-technical stakeholders - Work with cloud data services (AWS/Azure/GCP) for data ingestion, storage, and processing *(nice to have)* **Qualifications Required:** - 5+ years of experience - Strong SQL skills with the ability to write complex queries - Solid understanding of Data Warehousing concepts - Hands-on experience with ETL processes and data transformation logic - Good knowledge of Data Modeling (dimensional & relational) - Experience in Data Mapping and documenting S2T specifications - Strong analytical and problem-solving skills - Excellent communication and documentation abilities In addition, exposure to cloud data platforms like AWS (Redshift, Glue, Athena, S3), Azure (Synapse, Data Factory, Databricks), GCP (BigQuery, Dataflow, Pub/Sub), experience with BI/reporting tools (Tableau, Power BI, Looker), and a basic understanding of data governance and metadata management are considered *Nice to have*.,

Role Overview: As a Retail Specialized Data Scientist at Level 9 in the SnC GN Data & AI team, you will be responsible for utilizing advanced analytics, machine learning, and statistical modeling techniques to support data-driven decision-making in the retail sector. Your role will involve collaborating with various teams such as marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should possess experience in retail analytics and demonstrate the ability to transform data into actionable insights. Key Responsibilities: - Leverage Retail Knowledge: Utilize your in-depth understanding of the retail industry, including merchandising, customer behavior, and product lifecycle, to design AI solutions that cater to crucial retail business requirements. - Gather and clean data from diverse retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms such as classification, clustering, regression, and deep learning to improve predictive models. - Utilize AI-driven techniques for personalization, demand forecasting, and fraud detection. - Implement advanced statistical methods to optimize existing use cases and develop new products to address emerging challenges and use cases. - Stay abreast of the latest trends in data science and retail technology. - Collaborate effectively with executives, product managers, and marketing teams to translate insights into actionable business strategies. Qualifications Required: - A solid understanding of retail industry dynamics, encompassing key performance indicators (KPIs) like sales trends, customer segmentation, inventory turnover, and promotions. - Strong communication skills to convey complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. - Attention to detail to ensure data quality, accuracy, and consistency while handling large, complex datasets. - Proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). - Expertise in supervised and unsupervised learning algorithms. - Minimum 3 years of experience in the field. - Educational background in Data Science, Statistics, Computer Science, Mathematics, or related disciplines. Note: The job description does not include any additional details about the company.,

As a Senior Data Analyst at ENTRA SOLUTIONS PVT LTD, your role will involve analyzing complex data sets to provide valuable insights and support data-driven decision-making. You will collaborate with various teams, maintain data integrity, and mentor junior analysts. Key Responsibilities: - Collect, clean, and analyze large data sets to identify trends and patterns - Develop and maintain dashboards and reports for stakeholders - Collaborate with cross-functional teams to understand data needs and provide insights - Present findings and recommendations to senior management - Ensure data integrity and accuracy in all analyses - Mentor junior analysts and provide guidance on best practices Qualifications: - Bachelor's degree in Data Science, Statistics, Mathematics, or a related field - Minimum of 5 years of experience in data analysis or a related role - Proven track record of delivering actionable insights from data - Experience in a leadership or mentoring role is a plus Skills: - Proficient in DBT (Data Build Tool) (Must Have) - Proficient in Databricks and SQL any data visualization tool - Strong analytical and problem-solving skills - Experience with statistical analysis and modeling - Knowledge of data warehousing concepts - Excellent communication and presentation skills - Ability to work collaboratively in a team environment In addition to a competitive salary, as a Senior Data Analyst with us, you will have access to a full benefits package, PTO, and career growth opportunities. ENTRA SOLUTIONS PVT LTD is an equal employment opportunity employer, committed to providing a fair and inclusive work environment for all qualified applicants.,

Role Overview: As a Senior Technical Architect specializing in Data Science & Agentic AI, you will play a crucial role in leading the end-to-end modeling lifecycle. Your main responsibilities will include problem framing, experiment design, production deployment, and monitoring. You will be tasked with setting up the technical architecture for ML/GenAI and agentic systems. While collaborating with DE/Platform teams, your primary focus will be on modeling excellence, MLOps, and AI solution architecture to impact business KPIs positively. Key Responsibilities: - Own the technical vision for data-science initiatives and translate ambiguous business goals into modellable problems, KPIs, and NFRs/SLOs. - Define reference architectures for classical ML, deep learning, and agentic GenAI, including model registry, evaluation harness, safety/guardrails, and observability. - Lead problem decomposition, feature strategy, experiment design, error analysis, and model iteration. - Architect CI/CD for models, design monitoring for accuracy, drift, data integrity, latency, cost, and safety, and orchestrate RAG pipelines and feedback loops for continuous improvement. - Partner with various stakeholders to align roadmaps, provide technical mentorship to data scientists/ML engineers, and ensure solutions are operable. - Embed model governance, champion human oversight for agentic systems, and support GDPR/ISO/SOC2 requirements. Qualifications Required: - 14-20 years of experience delivering AI/ML in production, with at least 5 years in an architect/tech-lead capacity. - Proficiency in Python and ML stack (PyTorch and/or TensorFlow), strong SQL skills, and software engineering fundamentals. - Hands-on experience architecting scalable DS solutions on AWS/Azure/GCP, utilizing Docker and Kubernetes. - Expertise in MLOps tools such as MLflow/Kubeflow, model registry, pipelines, feature stores, and real-time/batch serving. - Depth across traditional ML and DL areas like NLP, CV, speech, time-series, recommendation, clustering/segmentation. - Excellent communication and stakeholder leadership skills, guiding cross-functional teams to deliver value. Additional Company Details (if available): Srijan, a Material company, is a renowned global digital engineering firm known for solving complex technology problems with deep expertise and strategic partnerships with top-tier technology companies.,

As a Senior Associate in Digital RM Data Analytics at EY, you will play a crucial role in managing internal risks associated with new client engagements and ongoing audit activities. You will be part of the Risk Management team, which acts as a Center of Excellence for standardized quality and compliance activities. **Role Overview:** You will be a key member of the Digital RM team at GDS, responsible for delivering advanced analytics, business intelligence, and technological support for Global RM & Risk Management Services. Your role will involve deploying analytics tools for real-time risk monitoring, streamlining processes, driving automation, and ensuring data governance and security. **Key Responsibilities:** - Collaborate with global teams and internal stakeholders to optimize processes and develop innovative solutions - Utilize data analytics tools to identify efficiencies, analyze data trends, and present insights for strategic decision-making - Work on systems analysis and design to enhance data relationships and integrations - Communicate effectively with cross-functional teams and provide analytical support - Drive operational excellence by challenging existing practices and proposing improvements - Synthesize complex information into impactful messages and promote data-driven insights **Qualifications Required:** **Essentials:** - Graduation/Postgraduation with 3-5 years of experience in a global corporate setting - Proficiency in SQL, Python, and MS Fabric tools - Excellent English communication skills and ability to summarize complex concepts for senior stakeholders - Strong knowledge of MS Office Suite - Ability to work independently and collaborate effectively with diverse teams **Preferred:** - Experience with XML, R, and SAS - Knowledge of data security and process mining - Creative visualization skills and passion for digitization and automation - Curiosity and willingness to experiment with new technologies **Additional Details:** You will have the opportunity to work in a fast-paced, innovative culture at EY, collaborating with global executive teams to strengthen compliance frameworks. EY Global Delivery Services offers a dynamic and inclusive environment where you can develop your skills and contribute to building a better working world. Join EY to be part of a team that values trust, respect, and continuous learning, providing opportunities to excel and grow in a diverse and inclusive culture.,

As a Senior Technical Program Manager for Data Science at Mastercard, you will play a crucial role in managing a wide variety of data science projects within the Security Solutions Data Science organization. Your responsibilities will involve interacting with data scientists, product managers, engineers, and senior leaders to deliver complex projects efficiently. You will define roadmap deliverables, develop execution plans, align dependencies, track progress, anticipate risks, make sound trade-off decisions, and translate technical expressions into business terminology. Additionally, you are expected to be detail-oriented, possess a solid technical background, and demonstrate excellent problem-solving skills. Key Responsibilities: - Act as the primary liaison between product and data science, managing day-to-day planning and execution of data science projects throughout the entire engagement process - Serve as the first point of contact for your teams or business line/service and provide accurate information about the project status to the right audience at the right time - Establish strong partnerships with product and technology teams to ensure alignment with data science efforts - Translate technical approaches and outcomes into business language effectively - Understand the business strategy and design approaches within product, program, or domain to be credible and influential with the teams you work with - Clearly articulate scope, timelines, dependencies, owners, actions, risks, and mitigations, and report progress to teams and senior leadership regularly - Collaborate with data scientists and engineering teams to enhance ways of working and identify/mitigate risks or issues that may impact the plan - Conduct meaningful retrospectives and create action plans to implement changes at the team level Qualifications Required: - Experience in project management, operating autonomously across multiple teams, with critical thinking and thought leadership skills - Ability to make trade-off decisions by considering business goals, technical platform strategy, customer experience, and maintainability - Track record of data-driven decision making and applying continuous improvement methodologies - Proficiency in building relationships, influencing dependent teams, and commanding respect across the organization - Strong organization, interpersonal, administrative, and problem-solving skills - Excellent communication skills at all levels of the organization - Capability to work independently with a collaborative nature - Ability to navigate a matrix organization Please note that at Mastercard, all staff are expected to embody the "Mastercard Way" cultural values, which include owning it, simplifying it, having a sense of urgency, taking thoughtful risks, unlocking potential, and being inclusive with a relentless focus on customers. Additionally, as part of your corporate security responsibility, you are required to abide by Mastercard's security policies, ensure the confidentiality and integrity of accessed information, report any suspected security violations or breaches, and complete all mandatory security trainings as per Mastercard's guidelines.,

As a Senior Machine Learning Scientist at Expedia Group, your role will involve designing cutting-edge machine learning algorithms to enhance the customer experience in the travel domain. You will focus on developing state-of-the-art solutions for post-booking recommendations and customer service use cases, addressing technical challenges and optimizing data pipelines to drive business growth. Your expertise in statistics, machine learning, and causal inference will be instrumental in creating effective solutions for travelers and partners worldwide. **Key Responsibilities:** - Design and implement end-to-end data science solutions for complex business problems. - Apply advanced machine learning techniques such as supervised, unsupervised, and reinforcement learning. - Optimize data pipelines and storage environments across cloud and on-premise systems. - Translate business requirements into robust models and actionable insights. - Mentor junior data scientists and contribute to the technical community through blogs, talks, and open-source contributions. - Collaborate cross-functionally to align data science initiatives with broader business goals. - Ensure ethical AI practices and apply core product management principles in solution design. **Qualifications Required:** - Bachelor's, Master's, or PhD in a technical or scientific discipline (or equivalent experience) - 7+ years of experience with a Bachelor's degree, 5+ years with a Master's degree, or 4+ years with a PhD - Led 2+ long-term projects spanning multiple quarters - Built and maintained multiple production-grade data science products - Expertise in supervised, unsupervised, and reinforcement learning - Proficiency in Python, Java, and SQL - Experience in feature engineering, training data management, and data visualization - Strong business acumen, communication skills, critical thinking, and problem-solving abilities - Talent assessment, coaching, stakeholder management, and project delivery skills - Knowledge of AI ethics and product management principles If you require any accommodations during the application process due to a disability or other health conditions, please contact our Recruiting Accommodations Team. Expedia Group is committed to fostering an inclusive culture where differences are celebrated, and everyone has the opportunity to thrive. Join us in shaping the future of travel and making a positive impact on millions of customers and partners worldwide.,

As a Data Scientist + Instructor AI/ML at our Computer Science Department, your role involves a combination of hands-on technical expertise and academic responsibilities. You will be designing and delivering practical, project-based courses in AI/ML, mentoring students in core Data Science and AI/ML concepts, and collaborating with academic leaders and industry partners to ensure curriculum relevance. Your passion for Artificial Intelligence and Machine Learning will be crucial in shaping the next generation of tech talent. Key Responsibilities: - Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML, covering topics such as Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, and GenAI. - Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculum to reflect current industry tools, techniques, and best practices, incorporating your professional experience and case studies. - Mentor Student Projects: Guide students through hands-on AI/ML projects, providing technical direction, code reviews, and feedback based on industry standards. - Guide & Mentor Students: Advise students on developing practical skills, understanding career paths in AI/ML, and preparing for internships and job placements. - Stay Current: Bring the latest AI/ML research, tools, and industry trends into the classroom. - Collaborate: Work closely with other expert faculty and staff to create a unified and effective learning experience. - Assess Practical Skills: Design and evaluate assignments, projects, and assessments focused on real-world applications. Qualifications and Requirements: - Bachelors or Masters degree in Computer Science, Engineering, Data Science, AI/ML, or related field. (PhD is valued but not mandatory.) - 7+ years of direct, hands-on professional experience in the tech industry as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/ML development and deployment. - Proven Industry Track Record: Demonstrated experience in building, training, and deploying machine learning models (including deep learning) for real-world problems. - Deep AI/ML Understanding: Strong grasp of core ML algorithms classical & deep learning (CNNs, RNNs, Transformers), model evaluation, statistics, and awareness of current research/industry trends. - Passion for Teaching/Mentoring: Ability to explain complex concepts clearly and guide others. Prior mentoring, corporate training, technical workshops, or project supervision experience is highly relevant. Required Skills: - Technical: Expert-level Python programming. - Proficiency with data science libraries (Pandas, NumPy, Scikit-learn). - Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch). - Strong SQL and data handling skills. - Understanding of ML Ops practices and tools (Git, Docker, AWS/GCP/Azure). - Knowledge of key AI areas (NLP, Computer Vision, Generative AI/LLMs). - Soft Skills: Strong communication, mentoring ability, collaboration, and a genuine passion for education. Good-to-Have: - Prior teaching experience at the undergraduate or graduate level. - Familiarity with modern teaching methodologies and academic.,

Role Overview: You will be part of a LiveOps team in QuantumBlack, working alongside the LiveOps Lead and LiveOps Engineer (Data Science) to maintain and enhance data pipelines within the company. As a Senior Data Engineer, you will play a critical role in supporting DE pipelines, ensuring stability, continuity, and availability of models while providing rapid response to incidents and user queries. Your responsibilities will include monitoring data pipelines for efficiency, collecting feedback from end-users, assetizing data pipelines for re-usability, identifying innovative data ingestion techniques, ensuring data governance compliance, and delivering solutions within agreed timelines and quality standards. Key Responsibilities: - Support DE pipelines and manage work to ensure stability and availability of models - Monitor data pipelines for efficiency and identify areas requiring maintenance - Collaborate with the scrum master to develop intervention plans based on feedback from end-users - Maximize re-usability of core components in data pipelines - Identify and implement innovative data ingestion techniques for optimized run-time - Enforce Data Governance rules and identify risks hindering compliant data use - Own and prioritize individual incidents, delivering solutions within deadlines and quality standards - Provide documentation to agreed standards and provide regional cover and support - Identify proactive strategies to prevent future data problems and improve solution quality - Monitor and alert on incidents, contribute to Service Improvement items including incident reduction and automation Qualifications Required: - Graduate or postgraduate degree in computer science, engineering, applied mathematics, quantitative social sciences, or related field - 2-5 years of relevant industry analytics experience - Knowledge of ITIL processes - Hands-on experience with Python, Spark, SQL/MSSQL Database - Working knowledge of monitoring tools like Grafana, Splunk; familiarity with Kedro is helpful - Understanding of JIRA, Service Now tools - Good to have experience with cloud providers such as AWS/Azure/GCP - Effective communication skills to interact with individuals at all levels within an organization - Familiarity with scheduling tools like Airflow, Argo would be advantageous Company Details: The company fosters a high-performance culture where your drive, determination, and curiosity are valued. You will have access to continuous learning opportunities, a voice that matters from day one, a global community of diverse colleagues, and world-class benefits to support your holistic well-being and professional growth.,

As a Senior Data Engineer at QuantumBlack, you will be an integral part of the LiveOps team, collaborating with the LiveOps Lead and the LiveOps Engineer (Data Science) to maintain and enhance data pipelines within the organization. Your primary responsibility will be to ensure the organic growth of solutions developed, emphasizing re-usability and ease of integration to facilitate quicker data access and reduced time-to-solution for new data initiatives. Key Responsibilities: - Support DE pipelines and oversee the work to ensure stability, continuity, and availability of models, while providing rapid responses to incidents and escalated user queries. - Monitor existing data pipelines for efficiency KPIs to proactively identify areas requiring maintenance. - Collaborate with the scrum master to develop an intervention plan based on issues and feedback reported by end-users. - Optimize data pipelines by assetizing them for re-usability in other data initiatives. - Identify innovative data ingestion and preparation techniques to enhance runtime and robustness of data pipelines. - Enforce Data Governance rules and proactively identify risks that may affect compliant data usage. - Prioritize individual incidents, deliver solutions within agreed deadlines and quality standards, and update key stakeholders regularly. - Provide regional cover and support, offering expertise and specialized domain knowledge to resolve key incidents during business hours. - Develop proactive remedial strategies to prevent future data problems and enhance solution quality. - Implement proactive and reactive monitoring and alerting processes. - Contribute to individual Service Improvement items, including incident reduction and automation. Qualifications and Skills: - Graduate or postgraduate degree in computer science, engineering, applied mathematics, quantitative social sciences, or a related field with 2-5 years of relevant industry analytics experience. - Knowledge of ITIL processes. - Proficiency in Python and Spark with hands-on experience in SQL/MSSQL Database. - Familiarity with monitoring tools like Grafana and Splunk; working knowledge of Kedro is advantageous. - Understanding of JIRA and Service Now tools. - Good to have experience with any cloud provider (AWS/Azure/GCP) and scheduling tools like Airflow or Argo. - Effective communication skills to convey complex ideas efficiently.,

Role Overview: As the Senior Director of Data Science, Analysis, & Visualization at Alkami, you will be leading the development and scaling of advanced analytics capabilities. Your primary responsibility will involve shaping the strategy, roadmap, and execution of machine learning, predictive analytics, and business intelligence initiatives within Alkami's digital banking and marketing ecosystem. This executive role will require you to oversee three core areas: Data Science, Data Analysis, and Visualization & Reporting. Key Responsibilities: - Define and drive Alkami's strategy for data science, analytics, and reporting, aligning with corporate priorities around personalization, engagement, and monetization. - Act as the senior-most leader for data science and analytics, representing these domains in executive forums and cross-functional planning. - Build and manage a high-performance organization across data scientists, analysts, and visualization specialists (~10-15 team members). - Collaborate across teams to embed analytics deeply into the product lifecycle, ensuring data tools and models are accessible, scalable, and aligned with both internal product needs and external client success. - Lead the development of machine learning models for customer scoring, churn prediction, cross-sell/upsell, segmentation, and prospect targeting. - Operationalize AI/ML outputs into platform features, champion model reliability, monitoring, and explainability. - Drive innovation in predictive and prescriptive analytics by continuously evaluating emerging ML technologies and methods. - Lead the development of dashboards and visualization tools that provide actionable insights to marketing, product, and executive teams. - Oversee platform migration to modern, AI-capable BI environments and develop self-service analytics capabilities for internal teams and clients. - Drive adoption and usage of data tools across the organization by designing user-friendly, role-based experiences. Qualifications Required: - 15+ years of experience in data science, analytics, or related fields, with 7+ years in a senior leadership role managing multidisciplinary teams. - Demonstrated success leading AI/ML initiatives from strategy through deployment in production environments, preferably in SaaS or fintech. - Deep technical expertise in machine learning, statistical modeling, and data visualization. - Proven ability to manage the full analytics lifecycle and strong command of tools like Python, SQL, R, and modern data stack components. - Experience with cloud-based ML platforms and MLOps. - Track record of mentoring senior data leaders and building scalable data teams. - Ability to communicate complex analytical concepts to executive audiences in clear, business-focused language. - Strong business acumen with a passion for solving real-world problems through data. - Bachelors degree in Data Science, Computer Science, Mathematics, or related field; Masters or Ph.D. preferred. Preferred Qualifications: - Experience in financial services, banking technology, or martech. - Familiarity with customer data platforms, segmentation frameworks, and digital engagement KPIs. - Understanding of data privacy and compliance frameworks.,