2 Arima Jobs nearby Ghaziabad

As Manager of Data Science at A&M GCC PI Supply Chain team, you will contribute in the following key areas: - Develop and automate data pipelines using Python for ingestion, cleansing, and transformation of supply chain data - Design predictive analytics models in Python (e.g., demand forecasting, inventory optimization) using libraries such as pandas, scikit-learn, stats models, and Prophet - Implement anomaly detection models to flag irregularities in procurement costs, delivery timelines, and inventory movements - Develop end-to-end ETL workflows for integrating data from SAP, SQL databases, and Excel-based trackers - Use Python for simulation of what-if scenarios in logistics and supply planning - Conduct Hyper Parameter tuning to enhance the performance of models - Design A/B tests and apply causal inference techniques for business impact analysis - Work with cloud platforms (AWS, GCP, Azure) and tools such as S3, Databricks - Create interactive visualizations and dashboards using Plotly, Seaborn, and Power BI for communicating insights In terms of qualifications, you should meet the following criteria: - Minimum of 6-11 years of experience in data science / modeling for functions across supply chain, i.e., logistics, transportation, distribution strategy, or downstream supply chain execution roles - Hands-on experience of minimum 3-4 years in Python with focus on statistical analysis and machine learning - Previous advisory experience from a top-tier strategy firm, niche logistics consulting firm, or Big-4 consultancy preferred - Bachelor's degree in engineering, logistics, supply chain, or a related field - Master's degree in Computer Science / Operations Research / Industrial Engineering is preferred - Strong storyboarding skills to translate operational insights into impactful client presentations - Excellent communication and interpersonal skills with high motivation to drive logistics transformation - Ability to manage multiple logistics-focused engagements and meet tight deadlines - Experience in KPI tracking and performance dashboards - Strong analytical, quantitative, and root-cause problem-solving skills Please note that A&M is a global consulting firm with a culture that prioritizes employee experience, continuous learning, and personal development. The company values inclusiveness, diversity, and fosters a culture of meritocracy. As part of the team, you will have access to top-notch training and learning opportunities to advance your career. As Manager of Data Science at A&M GCC PI Supply Chain team, you will contribute in the following key areas: - Develop and automate data pipelines using Python for ingestion, cleansing, and transformation of supply chain data - Design predictive analytics models in Python (e.g., demand forecasting, inventory optimization) using libraries such as pandas, scikit-learn, stats models, and Prophet - Implement anomaly detection models to flag irregularities in procurement costs, delivery timelines, and inventory movements - Develop end-to-end ETL workflows for integrating data from SAP, SQL databases, and Excel-based trackers - Use Python for simulation of what-if scenarios in logistics and supply planning - Conduct Hyper Parameter tuning to enhance the performance of models - Design A/B tests and apply causal inference techniques for business impact analysis - Work with cloud platforms (AWS, GCP, Azure) and tools such as S3, Databricks - Create interactive visualizations and dashboards using Plotly, Seaborn, and Power BI for communicating insights In terms of qualifications, you should meet the following criteria: - Minimum of 6-11 years of experience in data science / modeling for functions across supply chain, i.e., logistics, transportation, distribution strategy, or downstream supply chain execution roles - Hands-on experience of minimum 3-4 years in Python with focus on statistical analysis and machine learning - Previous advisory experience from a top-tier strategy firm, niche logistics consulting firm, or Big-4 consultancy preferred - Bachelor's degree in engineering, logistics, supply chain, or a related field - Master's degree in Computer Science / Operations Research / Industrial Engineering is preferred - Strong storyboarding skills to translate operational insights into impactful client presentations - Excellent communication and interpersonal skills with high motivation to drive logistics transformation - Ability to manage multiple logistics-focused engagements and meet tight deadlines - Experience in KPI tracking and performance dashboards - Strong analytical, quantitative, and root-cause problem-solving skills Please note that A&M is a global consulting firm with a culture that prioritizes employee experience, continuous learning, and personal development. The company values inclusiveness, diversity, and fosters a culture of meritocracy. As part of the team, you will have access to top-notch training and learning opportunities to advan

Role Overview: As a Senior Analyst-Enterprise SaaS specializing in the Indian power sector, your role will involve the following responsibilities: Key Responsibilities: - Developing Optimization models for the Power portfolio of State Utilities using GAMS based on Resource Adequacy guidelines. - Creating, implementing, and optimizing machine learning models (such as LSTM, XG Boost, ARIMA, SARIMA, LR, Ridge, Lasso RF) for demand and price forecasting, anomaly detection, etc. - Collaborating with cross-functional teams to integrate machine learning models into the production environment. - Managing and optimizing large-scale databases using SQL and NoSQL (MongoDB). - Building and maintaining financial models to assess and manage energy portfolios, risk assessment, and investment strategies. - Analyzing market trends, regulatory impacts, and economic factors influencing the Indian power sector. - Developing insightful and interactive visualizations using Python, Advanced Excel, Tableau, and Power BI. - Creating and maintaining dashboards for meaningful reports that monitor key performance indicators and model outputs. - System (Data) automation using VBA and Macros. - Hands-on experience in Short/Medium/Long Term Load Forecasting and Price Forecasting. - Utilizing advanced visualization techniques to support decision-making and stakeholder communication. Qualification Required: - Developing models for Power Portfolio Optimization using GAMS. - Expertise in time series analysis and forecasting techniques using machine learning. - Managing and optimizing databases like SQL and NoSQL (MongoDB). - Utilizing Python libraries like Pandas, Scipy, TensorFlow, scikit-learn for building forecasting models. - Proficiency in Advanced Excel, Power BI, VS-Code, and various tools for data analysis purposes. Additional Details: Your base location will be New Delhi, with the possibility of travel for pursuing various opportunities. The remuneration structure includes a motivation-based and competitive reward package.,

As a Data Scientist, you will play a crucial role in utilizing your expertise in various tools and techniques to derive insights from data. Your primary responsibilities will include: - Utilizing Classification techniques such as Decision Trees and SVM, Distance metrics like Hamming, Euclidean, and Manhattan Distance, as well as Forecasting methods like Exponential Smoothing, ARIMA, and ARIMAX. - Implementing ML Frameworks including TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet for model development. - Conducting Statistical analysis and computing using tools like Python, PySpark, R, R Studio, SAS, and SPSS. - Applying Regression models like Linear and Logistic Regression, and conducting Hypothesis Testing using T-Test and Z-Test. - Familiarity with Probabilistic Graph Models and tools such as KubeFlow and BentoML. Qualifications required for this role include proficiency in the mentioned tools and techniques, along with a strong background in data analysis and machine learning. Additionally, experience with Langraph and Agentic AI would be beneficial. Kindly note that the Job Description does not include any additional details about the company.,

Role Overview: As a Training Delivery & Content Development specialist, your primary responsibility is to conduct engaging training sessions on Blue Yonder's modules including Demand360 (D360), Inventory Optimizer (IO), and Fulfillment Module. You will be developing training materials and customizing content based on audience roles to ensure effective learning. Key Responsibilities: - Conduct engaging instructor-led (ILT) and virtual training sessions on Blue Yonder's modules: Demand360 (D360), Inventory Optimizer (IO), and Fulfillment Module. - Develop training materials such as user guides, presentations, exercises, and case studies. - Customize training content based on audience roles (planners, analysts, leadership). - Provide hands-on guidance on forecasting models, safety stock methodologies, and RecShip logic. - Assist in change management to drive Blue Yonder tool adoption. - Work with Blue Yonder implementation teams to align training with system configurations. - Gather feedback to enhance training programs and materials. - Stay updated on new Blue Yonder features and industry trends. Qualifications Required: - Experience in conducting training sessions on technical modules. - Strong knowledge of forecasting techniques, inventory optimization, and fulfillment strategies. - Proficiency in developing training materials and customizing content. - Excellent communication and interpersonal skills. - Ability to work collaboratively with teams and adapt to changes in a fast-paced environment.,

Role Overview: At o9 Solutions, we are looking for individuals who are eager to apply their expertise in machine learning techniques to contribute to our mission of digitally transforming planning and decision-making for enterprises. As part of our team, you will have the opportunity to work on cutting-edge AI-driven solutions that drive real value for our clients and the planet. Key Responsibilities: - Apply a variety of machine learning techniques such as clustering, regression, neural nets, and time series analysis to address real-world business challenges. - Develop and optimize models for demand sensing, forecasting, optimization, anomaly detection, simulation, and market intelligence. - Utilize the latest advancements in AI and ML to solve complex business problems effectively. - Collaborate with clients, project management, solution architects, consultants, and data engineers to ensure successful project delivery. Qualifications Required: - 4+ years of experience in time series forecasting using algorithms like exponential smoothing, ARIMA, and custom parameter tuning. - Experience in applied analytical methods in supply chain and planning domains. - Educational background in Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field. - Proficiency in Python and/or R for Data Science. - Deep knowledge of statistical and machine learning algorithms, scalable ML frameworks, and feature engineering. - Strong presentation and communication skills, with a focus on transparency and collaboration. Additional Details: o9 Solutions is a rapidly growing technology company with a strong entrepreneurial culture and a focus on making a significant impact in the industry. Our platform, the o9 Digital Brain, is at the forefront of digital transformations for leading global enterprises. We offer competitive salaries, stock options, and a supportive work environment that values diversity and work-life balance. Join us on our mission to drive innovation and change at scale. (Note: The company's expansion, valuation, and global presence are highlighted in the additional details section.),

You will be responsible for designing need-based business plans/strategies to maximize profitability and revenue generation for various commodities. Your role will involve spearheading complete business operations in the assigned region, ensuring ROI and profitability. You will formulate budgets and take measures to ensure optimum utilization of funds to achieve organizational objectives. Implementing marketing plans to capture optimal market share for the company's products will be crucial. Identifying and appointing reliable channel partners/dealers to deepen market penetration will also be part of your responsibilities. Monitoring dealers" performance as per company policies and ensuring adequate stock at the dealer's end will be essential. Analyzing market trends/requirements and devising measures to counter competition will be key. Interacting with customers to gather feedback on product utilities and providing quick and effective service will be important. Additionally, leading and monitoring team members" performance to ensure operational efficiency and target achievement will be required. Qualifications: - Experience and knowledge of having worked and handled mineral resources. - Experience in trading business for products like Zircon, Ilmenite, RUTILE, etc. - Strong communication and customer service skills - Proven track record in sales and sales management - Experience in providing training to clients - Knowledge of the chemical industry or related field is a plus - Ability to build and maintain strong client relationships - Bachelor's degree in Business, Marketing, or related field Note: The job requires full-time, permanent commitment and the work location is in person at Chennai.,

Role Overview: As a Demand Planning Specialist with expertise in SAS Viya and a foundation in AI/ML-driven forecasting, your primary responsibility will be to generate accurate product and location-level forecasts using advanced statistical models, AI, and machine learning. These insights will play a crucial role in driving smarter decisions related to inventory, supply chain, and pricing strategies. Key Responsibilities: - Develop and maintain short and long-term demand forecasts using SAS Viya for Demand Planning. - Apply advanced statistical models and AI/ML techniques to enhance forecast accuracy and responsiveness. - Collaborate with cross-functional teams including supply chain, sales, pricing, and others to ensure alignment of demand plans with overall business objectives. - Clean, prepare, and analyze large datasets for forecasting and performance monitoring. - Build interactive dashboards and reports using SAS Visual Analytics and other relevant tools. - Provide support for scenario planning, sensitivity analysis, and process automation initiatives. - Continuously monitor and enhance forecast performance through KPIs and regular analytics reviews. Qualification Required: - 45 years of experience in demand planning, forecasting, or supply chain analytics. - Hands-on expertise with SAS Viya and SAS Intelligent Planning. - In-depth knowledge of statistical forecasting methods such as ARIMA, exponential smoothing, etc. - Proficiency in SAS programming, data preparation, and SAS Visual Analytics. - Familiarity with AI/ML techniques and tools for demand forecasting. - Strong analytical, communication, and problem-solving skills. - Working knowledge of Python or R for advanced analytics. - Prior experience working in cloud-based SAS environments.,

As a Data Scientist / Senior Data Scientist at Tiger Analytics, you will play a crucial role in designing, building, and deploying end-to-end forecasting models using statistical and machine learning techniques such as ARIMA, Prophet, deep learning models, and XGBoost. Your expertise in PySpark will be essential to process, clean, and engineer features from massive, distributed datasets. Analyzing large-scale datasets to identify trends, seasonality, and key drivers will enable you to translate complex analytical findings into clear, actionable business insights for stakeholders. Developing and maintaining automated data and forecasting pipelines in a production environment, implementing best practices for model monitoring, version control, and model performance tracking will be part of your responsibilities. Collaboration with cross-functional teams, presenting complex methodologies and results to technical and non-technical audiences, and staying up-to-date with industry trends and advancements in forecasting methodologies are key aspects of this role. **Key Responsibilities:** - Design, build, and deploy end-to-end forecasting models using statistical and machine learning techniques. - Utilize PySpark to process, clean, and engineer features from large, distributed datasets. - Analyze large-scale datasets to identify trends, seasonality, and key drivers. - Develop and maintain automated data and forecasting pipelines in a production environment. - Work closely with cross-functional teams to understand requirements and ensure solutions align with business goals. - Present complex methodologies and results to technical and non-technical audiences. - Stay up-to-date on industry trends and propose innovative solutions to improve forecast accuracy and efficiency. **Qualifications:** - 5+ years of professional experience in data science, forecasting, or advanced analytics. - Bachelor's or master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline. **Technical Skills:** - Expertise in Python with knowledge of relevant libraries. - Proficiency in PySpark for large-scale data manipulation and model building. - Strong knowledge of SQL for data extraction and analysis. - Experience with the Azure cloud platform and Data Bricks. In addition to the technical skills, soft skills such as problem-solving, analytical abilities, strong communication, and storytelling skills are crucial for success in this role. Your proactive and adaptable mindset, along with a continuous learning approach, will be valued in our fast-paced environment. Don't worry if you don't meet all the criteria today, as we believe in the unique skills and qualities each individual brings. Tiger Analytics is an equal opportunity employer with a diverse and inclusive culture that encourages growth and development based on individual aspirations. *Note: The designation and compensation packages will be commensurate with expertise and experience.* Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities.,

As an AI/ML Engineer, your responsibilities will include: - Experience with Data engineering & Data/ML pipelines for Analytics & AI/ML Models - Working with large sets of structured & unstructured data from disparate sources - Foundational acquaintance of Data Science & AI/ML models - Proficiency in SQL, Python, Spark, PySpark - Familiarity with Big Data systems such as the Hadoop Ecosystem (HDFS, Hive, MapReduce) - Working knowledge of analytics databases like Druid, and data visualization/exploration tools like Superset - Understanding of cloud platforms like AWS, Azure, or GCP - Version control using GIT Secondary Skills (desired/preferred): - Experience with Apache Airflow, Apache Oozie, Nifi - Knowledge of GCP cloud, Big Query, and GCP Big Data Ecosystem - Proficiency in Trino/Presto - Familiarity with forecasting algorithms such as Time Series (Arima, Prophet), ML (GLM, GBDT, XgBoost), Hierarchical model (Top Down, Bottom Up), DL (Seq2Seq, Transformer) & Ensemble methods - Domain expertise in retail/predictions/time series forecasting - Continuous Integration/Continuous Deployment (CI/CD) for Data Pipelines & AI/ML models - Experience with MLOps tools & frameworks such as MLflow, Kubeflow, or Vertex AI You should have a minimum of 2-5 years of experience in this field to be considered for this role. The role is based at Manyata Tech Park. As an AI/ML Engineer, your responsibilities will include: - Experience with Data engineering & Data/ML pipelines for Analytics & AI/ML Models - Working with large sets of structured & unstructured data from disparate sources - Foundational acquaintance of Data Science & AI/ML models - Proficiency in SQL, Python, Spark, PySpark - Familiarity with Big Data systems such as the Hadoop Ecosystem (HDFS, Hive, MapReduce) - Working knowledge of analytics databases like Druid, and data visualization/exploration tools like Superset - Understanding of cloud platforms like AWS, Azure, or GCP - Version control using GIT Secondary Skills (desired/preferred): - Experience with Apache Airflow, Apache Oozie, Nifi - Knowledge of GCP cloud, Big Query, and GCP Big Data Ecosystem - Proficiency in Trino/Presto - Familiarity with forecasting algorithms such as Time Series (Arima, Prophet), ML (GLM, GBDT, XgBoost), Hierarchical model (Top Down, Bottom Up), DL (Seq2Seq, Transformer) & Ensemble methods - Domain expertise in retail/predictions/time series forecasting - Continuous Integration/Continuous Deployment (CI/CD) for Data Pipelines & AI/ML models - Experience with MLOps tools & frameworks such as MLflow, Kubeflow, or Vertex AI You should have a minimum of 2-5 years of experience in this field to be considered for this role. The role is based at Manyata Tech Park.

As a Machine Learning Timeseries Analyst in this contract remote role, your main responsibility will be to analyze data, develop data models, and utilize statistical methods for interpreting timeseries data. Your strong communication skills will be crucial for effectively conveying insights and findings to stakeholders. Key Responsibilities: - Utilize ML & Stats techniques such as ARIMA, SARIMA, Prophet, Scikit-Learn for predictive analytics on timeseries data - Proficiency in tech tools like Python, MySQL, Tableau, Excel, SAP, and Kinaxis Rapid Response Planning Software - Demonstrate strong analytical skills, data analytics expertise, and statistical proficiency - Employ advanced knowledge of machine learning techniques in data modeling - Showcase excellent communication skills to effectively communicate insights - Work independently and remotely to meet project goals Qualifications Required: - Master's degree in Data Science, Computer Science, Statistics, or a related field - Prior experience in data analysis, data modeling, and machine learning techniques - Proficiency in ARIMA, SARIMA, Prophet, Scikit-Learn for timeseries analysis - Strong communication skills to convey complex findings effectively - Ability to work independently and remotely, demonstrating self-motivation and initiative (Note: Additional details about the company were not provided in the job description.),

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 a Senior Data Scientist, you will be responsible for leveraging your 10+ years of experience to build and optimize machine learning models using Python. Your strong Python skills in data analysis, statistics, data visualization, modeling, and computing will be crucial for success in this role. Key Responsibilities: - Building and optimizing machine learning models using Python - Utilizing Python libraries such as SKLearn, Pandas, Seaborn, PyTorch, Tensor Flow, Keras, Numpy, MatPlotLib, Scipy, Statsmodels, Arima, Arimax, and Sarimax - Experience with Jupyter notebook or related Notebook tools - Familiarity with Streamlit and SQL - Working knowledge of Javascript or Typescript Qualifications Required: - 10+ years of experience in data science - Proficiency in Python for data analysis, statistics, and visualization - Strong background in machine learning and model optimization - Familiarity with a variety of Python libraries - Experience with Jupyter notebook and SQL - Knowledge of Javascript or Typescript is a plus,

As a Hardware Engineer at Qualcomm India Private Limited, you will play a crucial role in planning, designing, optimizing, verifying, and testing electronic systems. Your responsibilities will include working on various systems such as circuits, mechanical systems, Digital/Analog/RF/optical systems, equipment and packaging, test systems, FPGA, and/or DSP systems. You will be instrumental in launching cutting-edge products by collaborating with cross-functional teams to develop solutions and meet performance requirements. Key Responsibilities: - Design and implement end-to-end data analytics workflows tailored to semiconductor engineering use cases. - Develop, train, and optimize ML models using supervised, unsupervised, and deep learning techniques. - Perform feature engineering, model evaluation, and hyperparameter tuning to improve model performance. - Build scalable data ingestion and transformation pipelines using Python and cloud-native tools. - Apply statistical analysis and visualization techniques to derive insights from large datasets. - Conduct time series analysis using methods such as ANOVA and other statistical techniques. - Experiment with GenAI platforms, LLMs, and RAG techniques to enhance model capabilities. - Collaborate with cross-functional teams to integrate ML models into engineering workflows and tools. - Document methodologies and provide technical guidance to internal teams. Qualification Required: - Masters degree in Computer Science, Data Science, or a related field. - Strong programming skills in Python or C++. - Solid understanding of data structures, algorithms, and software design principles. - Strong analytical and problem-solving skills. - Hands-on experience with supervised and unsupervised learning techniques (e.g., classification, clustering, dimensionality reduction). - Experience with deep neural network architectures including RNNs, and Transformers. - Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. - Proficiency in data analysis using Pandas, NumPy, and Matplotlib. - Statistical Analysis & Visualization - Feature Engineering & Model Evaluation - Understanding of GPU, CUDA & High performance Computing Frameworks & Methods. Preferred Qualifications: - PHD in Computer Science, Data Science, or a related field. - Experience in large Model Development & Training from the Scratch. - Familiarity with time series analysis methods including ANOVA, ARIMA, and seasonal decomposition. - Familiarity with SQL databases, ETL frameworks, and cloud platforms (e.g., AWS). - Knowledge of LLM integration frameworks (e.g., LangChain). - Hands-on experience with distributed computing and cloud-scale data processing. - Software Design & Architecture Qualcomm India Private Limited is focused on applying state-of-the-art AI and ML technologies to enhance engineering efficiency through intelligent automation, data-driven insights, and innovative tool development. If you are a passionate and technically strong engineer looking to drive innovation in chip design, qualification, and debug engineering, this is the perfect opportunity for you.,

As a Senior Consultant, Data Scientist in the Supply Chain Consulting team at NTT DATA, you will play a crucial role in developing and deploying cutting-edge supply chain solutions for leading organizations. Your primary responsibility will be to design and implement time series forecasting models for demand planning and other supply chain use cases using both traditional statistical models and modern machine learning techniques. **Responsibilities:** - Design, develop, and implement time series forecasting models for demand planning and other supply chain use cases. - Apply statistical techniques such as ARIMA, ETS etc for effective & strong baseline modeling. - Implement and optimize machine learning algorithms (e.g., Boosting methods like LightGBM, CatBoost etc) to improve forecast accuracy. - Collaborate with clients to understand business problems and translate them into data science solutions. - Contribute to broader AI/ML initiatives across supply chain functions, including anomaly detection, inventory optimization, and scenario modeling. - Communicate results effectively to technical and non-technical stakeholders. - Work closely with digital supply chain platforms such as o9, Blue Yonder, or similar (experience preferred). **What You'll Bring:** - 5 to 8 years of hands-on experience in Data Science or Analytics, preferably in supply chain or operations domains. - Strong expertise in time series forecasting, with proven experience implementing models like ARIMA, ETS, etc. - Solid experience in applying machine learning techniques such as boosted trees, random forests, etc. - Proficiency in Python (including libraries like pandas, scikit-learn, statsmodels/StatsForecast/DARTS etc) and SQL. - Exposure to or experience with digital supply chain tools (e.g., o9, Blue Yonder) is highly desirable. - Strong problem-solving and communication skills with the ability to manage client interactions independently. - Understanding of MLOps, model deployment, or cloud platforms (Azure, AWS) is a plus. NTT DATA is a $30 billion trusted global innovator of business and technology services, serving 75% of the Fortune Global 100. They are committed to helping clients innovate, optimize, and transform for long-term success. With diverse experts in more than 50 countries and a robust partner ecosystem, NTT DATA provides services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is a leading provider of digital and AI infrastructure worldwide and is part of the NTT Group, investing over $3.6 billion each year in R&D to support organizations and society in confidently transitioning into the digital future. Visit [NTT DATA](https://us.nttdata.com) for more information.,

As a Senior Associate in data analysis at PwC, you will play a crucial role in leveraging data to drive insights and support clients in making informed business decisions. Your responsibilities will include utilizing advanced analytics techniques to extract insights from large datasets, manipulating data, creating visualizations, and employing statistical modeling to solve complex business problems. Key Responsibilities: - Proven expertise in supply chain analytics including demand forecasting, inventory optimization, logistics, segmentation, and network design - Hands-on experience with optimization methods like linear programming, mixed integer programming, scheduling optimization, and using third-party optimization solvers such as Gurobi - Proficiency in forecasting techniques like Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats, and machine learning techniques (supervised and unsupervised) - Strong command of statistical modeling, testing, and inference - Proficient in GCP tools like BigQuery, Vertex AI, Dataflow, and Looker - Building data pipelines and models for forecasting, optimization, and scenario planning - Strong skills in SQL and Python programming, with experience deploying models in the GCP environment - Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to Have: - Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools like Cloud Composer - Strong communication and stakeholder engagement skills at the executive level Qualifications Required: - BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute,

Qualcomm India Private Limited is looking for a Hardware Engineer to join their Engineering Group, specifically focusing on Hardware Engineering. As a Qualcomm Hardware Engineer, you will be responsible for planning, designing, optimizing, verifying, and testing electronic systems, circuits, mechanical systems, and equipment to launch cutting-edge products. You will collaborate with cross-functional teams to develop solutions and meet performance requirements. Key Responsibilities: - Design and implement end-to-end data analytics workflows tailored to semiconductor engineering use cases. - Develop, train, and optimize ML models using supervised, unsupervised, and deep learning techniques. - Perform feature engineering, model evaluation, and hyperparameter tuning to improve model performance. - Build scalable data ingestion and transformation pipelines using Python and cloud-native tools. - Apply statistical analysis and visualization techniques to derive insights from large datasets. - Conduct time series analysis using methods such as ANOVA and other statistical techniques. - Experiment with GenAI platforms, LLMs, and RAG techniques to enhance model capabilities. - Collaborate with cross-functional teams to integrate ML models into engineering workflows and tools. - Document methodologies and provide technical guidance to internal teams. Qualification Required: - Master's degree in Computer Science, Data Science, or a related field. - Strong programming skills in Python or C++. - Solid understanding of data structures, algorithms, and software design principles. - Strong analytical and problem-solving skills. - Hands-on experience with supervised and unsupervised learning techniques. - Experience with deep neural network architectures including RNNs and Transformers. - Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. - Proficiency in data analysis using Pandas, NumPy, and Matplotlib. - Familiarity with statistical analysis & visualization, feature engineering, and model evaluation. If you are a passionate engineer with a strong technical background, this role at Qualcomm offers the opportunity to work on advanced data analytics and machine learning models in the chip design, qualification, and debug engineering processes. You will play a key role in enhancing engineering efficiency through intelligent automation, data-driven insights, and innovative tool development.,

As a Data Scientist at mPokket, your role involves working with the data science team, planning projects, and building analytics models. You should possess a strong problem-solving ability and a knack for statistical analysis. Your main objective will be to align data products with business goals to enhance products and business decisions through effective data utilization. **Key Responsibilities:** - Overseeing the data scientists" team and data specialists. - Teaching, leading, and counseling colleagues on new techniques or solutions. - Collaborating with data and software engineers for deploying sciences and technologies across the company's ecosystem. - Conceiving, planning, and prioritizing data projects. - Building analytic systems and predictive models, while experimenting with new techniques. - Ensuring data projects align with organizational goals. **Qualifications Required:** - Master's degree in Computer Science, Operations Research, Econometrics, Statistics, or related technical field. - 2+ years of experience in solving analytical problems using quantitative approaches. - Proficiency in communicating quantitative analysis results. - Knowledge of relational databases and SQL. - Development experience in any scripting language (e.g., PHP, Python, Perl). - Familiarity with statistics (e.g., hypothesis testing, regressions). - Experience manipulating data sets through statistical software (e.g., R, SAS) or other methods. **Technical Skills - Must Have:** - Programming: Python (Preferred) / R. - ML Models: Regression (Linear, Logistic, Multinomial, Mixed effect), Classification (Random Forest, Decision tree, SVM), Clustering (K-Means, hierarchical, DB-Scan), Time series (ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS), Neural Networks (Deep learning), Naive Bayes, Excel, SQL. - Dimensionality Reduction: PCA, SVD, etc. - Optimization Techniques: Linear programming, Gradient Descent, Genetic Algorithm. - Cloud: Understanding of Azure / AWS offerings, setting up an ML pipeline in the cloud. **Good To Have:** - Visualization: Tableau / Power BI / Looker / QlikView. - Data Management: HDFS, Spark, Advanced Excel. - Agile Tools: Azure DevOps, JIRA, Pyspark, Big Data / Hive Database. - IDE: PyCharm. Please note that this job posting was by Debapti Roy from mPokket.,

You will be responsible for applying advanced forecasting methodologies to estimate sales and revenue for newly launched and pipeline pharmaceutical products. This will involve incorporating financial modeling and corporate finance principles into forecasting frameworks to support long-term strategic planning. You will need to develop robust, data-driven models that consider market dynamics, patient behavior, and competitive intelligence to generate accurate and actionable forecasts. Collaboration with marketing, commercial, and research teams is essential to ensure alignment of forecasts with strategic objectives and product positioning. Additionally, leveraging statistical, machine learning, and deep learning techniques will help uncover insights that inform launch strategies and optimize product performance. You will also partner with key business stakeholders to identify, scope, and execute predictive analytics initiatives that address critical business needs and deliver measurable value. It is important to maintain a strong understanding of the pharmaceutical landscape to provide objective, data-driven input into strategic decisions. Collaboration within the analytics team is key, as sharing knowledge and seeking feedback enhances the quality and impact of analytical deliverables. Staying current with emerging techniques and tools in predictive analytics ensures methodological rigor and adaptability in approach. Comfort with varied data sources and types is necessary to ensure seamless integration and analysis across structured and unstructured datasets. - Masters or Bachelor in Statistics, Economics, Data Sciences, Engineering, or quantitative related field. - Minimum of 5 years of working experience as a Data Scientist in the industry. - Deep and broad knowledge of Data Science methods and tools including Simulation model building principles, Machine Learning, and best practices: - Point Forecasting and Probabilistic Forecasting. - Agent-based Simulation Model using Anylogic. - Any type of simulation model experience (Good to have). - Statistical Forecasting: ARIMA, THETA, Exponential Smoothing. - ML-based Forecasting: GBM, LightGBM, XGBoost, Linear Regression. - DL-based Forecasting: DeepAR, NBEATS, LSTM, RNN. - Hierarchical Forecasting. - Cross-Validation: Rolling-window, Expanding-window, K-fold, Hold-out. - MLOps is also good to have skills. - Exposure to LLM or GPT good to have skills. You are expected to be strong in Python and SQL, with R & Java as a good-to-have. Strong communication skills are essential to bring Analytics to life by giving it zeal and making it applicable to the business. Keeping up-to-date on analytical, computational, and scientific advances is crucial to maximize your impact. An insatiable desire to learn, innovate, and challenge yourself for the benefit of patients is highly encouraged.,

As a Senior Consultant, Data Scientist in the Supply Chain Consulting team at NTT DATA, your role will involve designing and delivering cutting-edge supply chain solutions for leading organizations globally. Your primary focus will be on developing and deploying forecasting solutions using both traditional statistical models and modern machine learning techniques. Additionally, you will contribute to building AI/ML-driven solutions for various real-world supply chain challenges. **Responsibilities:** - Design, develop, and implement time series forecasting models for demand planning and other supply chain use cases. - Apply statistical techniques such as ARIMA, ETS, etc., for effective baseline modeling. - Implement and optimize machine learning algorithms (e.g., Boosting methods like LightGBM, CatBoost, etc.) to enhance forecast accuracy. - Collaborate with clients to comprehend business problems and translate them into data science solutions. - Contribute to broader AI/ML initiatives across supply chain functions, including anomaly detection, inventory optimization, and scenario modeling. - Communicate results effectively to technical and non-technical stakeholders. - Work closely with digital supply chain platforms such as o9, Blue Yonder, or similar (experience preferred). **What You'll Bring:** - 5 to 8 years of hands-on experience in Data Science or Analytics, preferably in supply chain or operations domains. - Strong expertise in time series forecasting, with proven experience in implementing models like ARIMA, ETS, etc. - Solid experience in applying machine learning techniques such as boosted trees, random forests, etc. - Proficiency in Python (including libraries like pandas, scikit-learn, statsmodels/StatsForecast/DARTS, etc.) and SQL. - Exposure to or experience with digital supply chain tools (e.g., o9, Blue Yonder) is highly desirable. - Strong problem-solving and communication skills with the ability to manage client interactions independently. - Understanding of MLOps, model deployment, or cloud platforms (Azure, AWS) is a plus. As part of NTT DATA, a trusted global innovator of business and technology services, we are committed to helping clients innovate, optimize, and transform for long-term success. With a diverse team of experts across more than 50 countries, we offer services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. Join us in shaping the digital and AI infrastructure of the future. Visit us at us.nttdata.com.,

As a Data Scientist at Lifease Solutions LLP, your main responsibility will be to develop machine learning and deep learning models for predicting match scores & outcomes, team & player performances, and statistics. You will also be involved in in-depth cricket analytics to analyze player form, team strengths, matchups, and opposition weaknesses. Additionally, you will work on data processing & engineering tasks, model deployment & MLOps, and performance metrics & model explainability. Key Responsibilities: - Develop ML/DL models for predicting match scores & outcomes, team & player performances, and statistics. - Implement time-series forecasting models (LSTMs, Transformers, ARIMA, etc.) for score predictions. - Train and fine-tune reinforcement learning models for strategic cricket decision-making. - Develop ensemble learning techniques to improve predictive accuracy. - Design models to analyze player form, team strengths, matchups, and opposition weaknesses. - Build player impact and performance forecasting models based on pitch conditions, opposition, and recent form. - Extract insights from match footage and live tracking data using deep learning-based video analytics. - Collect, clean, and preprocess structured and unstructured cricket datasets from APIs, scorecards, and video feeds. - Build data pipelines (ETL) for real-time and historical data ingestion. - Work with large-scale datasets using big data tools (Spark, Hadoop, Dask, etc.). - Deploy ML/DL models into production environments (AWS, GCP, Azure etc). - Develop APIs to serve predictive models for real-time applications. - Implement CI/CD pipelines, model monitoring, and retraining workflows for continuous improvement. - Define and optimize evaluation metrics (MAE, RMSE, ROC-AUC, etc.) for model performance tracking. - Implement explainable AI techniques to improve model transparency. - Continuously update models with new match data, player form & injuries, and team form changes. Qualification Required: - Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. - Strong experience in predictive modeling, deep learning, and data analytics. - Proficiency in Python programming and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Experience with big data tools such as Spark, Hadoop, or Dask. - Knowledge of cloud platforms like AWS, GCP, or Azure for model deployment. - Excellent communication and collaboration skills to work in a team environment.,