100 Time Series Jobs

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy, and that hasn't happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target's global team and has more than 4,000 team members supporting the company's global strategy and operations. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values diverse backgrounds. We believe your unique perspective is important, and you'll build relationships by being authentic and respectful. At Target, inclusion is part of the core value. We aim to create equitable experiences for all, regardless of their dimensions of difference. As an equal opportunity employer, Target provides diverse opportunities for everyone to grow and win. The People Analytics team's mission is to empower a data-driven approach to HR and people decisions regarding our global workforce. We are uniquely positioned to provide unbiased insights to unlock value and drive outcomes and to enable and influence HR and business strategy. The People Analytics team integrates into the business as strategic HR analytics partners and anticipates and uncovers stated or unstated needs. They use analytics expertise to test, measure, analyze, understand, and answer various business questions. The team provides reporting to help inform on the current state of the business and help facilitate processes at scale. They connect understanding across business and HR to deliver data-driven products and solutions, providing meaningful insights and recommendations. About the role: Our Data Analysts are expected to explore data, technologies, and the application of mathematical techniques to enable business insights. Data analysts accomplish this through a wide variety of skills including data wrangling, reporting, dashboarding, visualization, statistical analysis, modeling, and the presentation of recommendations and insight. Analysts work within an agile environment, which requires active participation in ceremonies to accomplish the team's goals. They also develop domain knowledge as they learn about their business area and support applying key data management principles like metadata management, data profiling, and documenting data lineage. Key Responsibilities: - Actively explore data for specific use cases. - Develop expertise in business domain and processes. - Create measurable insights from the data to be shared. - Develop metrics, measurement strategy, reports, and statistics. - Document calculations, code, and adhere to data management principles. - Validate and test data assets of others in the form of peer review. - Explore statistical analysis that could be applied to the data. - Perform descriptive statistics including mean, variance, median, correlation. - Apply insights and testing in partnership with business users. - Be an active participant in team meetings. - Lead agile ceremonies. - Ability to work independently to turn business problems into data solutions. - Serve as a thought leader and mentor on business domain and analytical techniques to elevate team performance. Qualifications: - BA/BS or equivalent experience. - 9+ years" work experience in data analysis or master's level education in business analytics, data science, etc. - Demonstrated leader in knowledge and application of data, reporting, and analytics. - Proficient with various programming languages - SQL, R, Python. - Proficient with relational and non-relational databases. - Strong domain-specific knowledge in Human Resources data and processes. - Prior experience in human resources or talent/people analytics industry. - Strong mathematical and statistical skills. - Excellent communication skills with the ability to speak to both business and technical teams. - Knowledge of AB Testing methods, time series, S&OP planning, Forecasting models, and analytics tools such as SQL, Excel, Hadoop, Hive, Spark, Python, R, Domo, Adobe Analytics, and/or equivalent technologies.,

As a Manager, Behavioral Modeler (Development/Validation) & Researcher Specialist at Genpact, you will be responsible for developing or validating Behavioral Models for banking and financial institutions, focusing on areas such as Financial Crime (Fraud or AML), Marketing Campaigns, and Adjudication models. Your role will involve working closely with the centralized advanced analytics team of banking or financial firms, interacting with various business units, auditors, and model development/validation teams to ensure compliance with Enterprise Modeling Governance standards. Your key responsibilities will include providing analytical support to mitigate risk, assessing data quality for model development, developing machine learning-based models, proposing recommendations to improve monitoring systems, conducting in-depth research on behavioral modeling policies, and contributing to the creation of whitepapers and artifacts. You will be expected to have hands-on experience in developing and validating models, risk management, and applying AI, ML, and Deep Learning techniques using tools such as SAS, Python, and R. The qualifications we seek in you include a Master's degree in a quantitative discipline, experience in statistical modeling, detailed knowledge of data analysis techniques, expertise in SQL, ETL, and strong scripting and automation skills. Additionally, you should possess strong client management, communication, and presentation skills, be self-driven, proactive, and have the ability to work under ambiguity and with minimal supervision. You should also have strong project management experience, the ability to lead projects and teams, and demonstrate expertise in communicating and coordinating across multiple business units. Preferred qualifications/skills include strong networking, negotiation, and influencing skills, as well as prior experience in financial crime and machine learning models. If you are a forward-thinking individual with a hunger for learning and a passion for turning innovative ideas into reality, we invite you to apply for this challenging and rewarding role at Genpact. Please note that this is a full-time position based in India-Kolkata, and the job posting was on Oct 7, 2024.,

Title: AI/ML Architect Location: Onsite Bangalore Experience: 10+ years Position Summary: We are seeking an experienced AI/ML Architect to lead the design and deployment of scalable AI solutions. This role requires a strong blend of technical depth, systems thinking, and leadership in machine learning , computer vision , and real-time analytics . You will drive the architecture for edge, on-prem, and cloud-based AI systems, integrating 3rd party data sources, sensor and vision data to enable predictive, prescriptive, and autonomous operations across industrial environments. Key Responsibilities: Architecture & Strategy Define the end-to-end architecture for AI/ML systems including time series forecasting , computer vision , and real-time classification . Design scalable ML pipelines (training, validation, deployment, retraining) using MLOps best practices. Architect hybrid deployment models supporting both cloud and edge inference for low-latency processing. Model Integration Guide the integration of ML models into the IIoT platform for real-time insights, alerting, and decision support. Support model fusion strategies combining disparate data sources, sensor streams with visual data (e.g., object detection + telemetry + 3rd party data ingestion). MLOps & Engineering Define and implement ML lifecycle tooling, including version control, CI/CD, experiment tracking, and drift detection. Ensure compliance, security, and auditability of deployed ML models. Collaboration & Leadership Collaborate with Data Scientists, ML Engineers, DevOps, Platform, and Product teams to align AI efforts with business goals. Mentor engineering and data teams in AI system design, optimization, and deployment strategies. Stay ahead of AI research and industrial best practices; evaluate and recommend emerging technologies (e.g., LLMs, vision transformers, foundation models). Must-Have Qualifications: Bachelor’s or Master’s degree in Computer Science, AI/ML, Engineering, or a related technical field. 8+ years of experience in AI/ML development, with 3+ years in architecting AI solutions at scale. Deep understanding of ML frameworks (TensorFlow, PyTorch), time series modeling, and computer vision. Proven experience with object detection, facial recognition, intrusion detection , and anomaly detection in video or sensor environments. Experience in MLOps (MLflow, TFX, Kubeflow, SageMaker, etc.) and model deployment on Kubernetes/Docker . Proficiency in edge AI (Jetson, Coral TPU, OpenVINO) and cloud platforms (AWS, Azure, GCP). Nice-to-Have Skills: Knowledge of stream processing (Kafka, Spark Streaming, Flink). Familiarity with OT systems and IIoT protocols (MQTT, OPC-UA). Understanding of regulatory and safety compliance in AI/vision for industrial settings. Experience with charts, dashboards, and integrating AI with front-end systems (e.g., alerts, maps, command center UIs). Role Impact: As AI/ML Architect, you will shape the intelligence layer of our IIoT platform — enabling smarter, safer, and more efficient industrial operations through AI. You will bridge research and real-world impact , ensuring our AI stack is scalable, explainable, and production-grade from day one.

We are looking for an experienced Senior Data Engineer to lead the development of scalable AWS-native data lake pipelines with a strong focus on time series forecasting and upsert-ready architectures. This role requires end-to-end ownership of the data lifecycle, from ingestion to partitioning, versioning, and BI delivery. The ideal candidate must be highly proficient in AWS data services, PySpark, versioned storage formats like Apache Hudi/Iceberg, and must understand the nuances of data quality and observability in large-scale analytics systems. Role & responsibilities Design and implement data lake zoning (Raw Clean Modeled) using Amazon S3, AWS Glue, and Athena. Ingest structured and unstructured datasets including POS, USDA, Circana, and internal sales data. Build versioned and upsert-friendly ETL pipelines using Apache Hudi or Iceberg. Create forecast-ready datasets with lagged, rolling, and trend features for revenue and occupancy modelling. Optimize Athena datasets with partitioning, CTAS queries, and metadata tagging. Implement S3 lifecycle policies, intelligent file partitioning, and audit logging. Build reusable transformation logic using dbt-core or PySpark to support KPIs and time series outputs. Integrate robust data quality checks using custom logs, AWS CloudWatch, or other DQ tooling. Design and manage a forecast feature registry with metrics versioning and traceability. Collaborate with BI and business teams to finalize schema design and deliverables for dashboard consumption. Preferred candidate profile 9-12 years of experience in data engineering. Deep hands-on experience with AWS Glue, Athena, S3, Step Functions, and Glue Data Catalog. Strong command over PySpark, dbt-core, CTAS query optimization, and partition strategies. Working knowledge of Apache Hudi, Iceberg, or Delta Lake for versioned ingestion. Experience in S3 metadata tagging and scalable data lake design patterns. Expertise in feature engineering and forecasting dataset preparation (lags, trends, windows). Proficiency in Git-based workflows (Bitbucket), CI/CD, and deployment automation. Strong understanding of time series KPIs, such as revenue forecasts, occupancy trends, or demand volatility. Data observability best practices including field-level logging, anomaly alerts, and classification tagging. Experience with statistical forecasting frameworks such as Prophet, GluonTS, or related libraries. Familiarity with Superset or Streamlit for QA visualization and UAT reporting. Understanding of macroeconomic datasets (USDA, Circana) and third-party data ingestion. Independent, critical thinker with the ability to design for scale and evolving business logic. Strong communication and collaboration with BI, QA, and business stakeholders. High attention to detail in ensuring data accuracy, quality, and documentation. Comfortable interpreting business-level KPIs and transforming them into technical pipelines.

Job Title: Data Scientist Turning Data into Decisions Location: Bengaluru | Experience: 25 Years | Type: Full-Time About the Role: Are you passionate about predicting the future with data? Do you thrive on uncovering patterns hidden in time series and driving impactful business decisions? We’re looking for a Data Scientist who’s part analyst, part engineer, and 100% curious. What You’ll Do: Forecast demand like a pro Optimize supply chains and uncover hidden trends Build smart ML models using Python, TensorFlow, or PyTorch Turn messy data into clear, actionable insight Collaborate with teams and tell compelling stories through dashboards Tech Toolkit: Time Series | Regression & A/B Testing Python | NumPy, Pandas, scikit-learn Tableau / Plotly / Matplotlib SQL | ETL Pipelines You’re a Perfect Fit If: You have 2+ years of hands-on Data Science experience You think in models and breathe in data You’re a storyteller with code and charts You love solving problems that make businesses smarter.

Position level: AI Specialist/Software engineering professional (Cant be a junior/fresher, needs to be middle to senior level person) Work Experience: Ideally, 4 to 5 years of working as a Data Scientist / Machine Learning and AI at a managerial position (end-to-end project responsibility). Slightly lower work experience can be considered based on the skill level of the candidate. About the job: Use AI-ML to work with data to predict process behaviors. Stay abreast of industry trends, emerging technologies, and best practices in data science, and provide recommendations for adopting innovative approaches within the product teams. In addition, championing a data-driven culture, promoting best practices, knowledge sharing, and collaborative problem-solving. Abilities: Knowledge about data analysis, Artificial Intelligence (AI), Machine Learning (ML), and preparation of test reports to show results of tests. Strong in communication with a collaborative attitude, not afraid to take responsibility and make decisions, open to new learning, and adapt. Experience with end-to-end process and used to make result presentation to customers. Technical Requirements: Experience working with real world messy data (time series, sensors, etc.) Familiarity with Machine learning and statistical modelling Ability to interpret model results in business context Knowledge of Data preprocessing (feature engineering, outlier handling, etc.) Soft Skill Requirements: Analytical thinking Ability to connect results to business or process understanding Communication skills Comfortable explaining complex topics to stakeholders Structured problem solving – Able to define and execute a structured way to reach results Autonomous working style – can drive a small project or parts of a project Tool Knowledge: Programming: Python (Common core libraries: pandas, numpy, scikit-learn, matplotlib, mlfow etc.); Knowledge of best practices (PEP8, code structure, testing, etc.) Code versioning (GIT) Data Handling: SQL; Understanding of data format (CSV, JSON, Parquet); Familiarity with time series data handling Infrastructure: Basic Cloud technology knowledge (Azure (preferred), AWS, GCP); Basic Knowledge of MLOps workflow Good to have: Knowledge of Azure ML, AWS SageMaker; Knowledge of MLOps best practices in any tool; Containerization and deployment (Docker, Kubernetes) Languages: English – Proficient/Fluent Location: Hybrid (WFO+WFH) + Availability to visit customer sites for meetings and work-related responsibilities as per the project requirement.

Machine Learning Engineer Python, with proficiency in ML libraries such as scikit-learn, TensorFlow, PyTorch Experience: 5+ years Location: Fujitsu India R&D Center Position Type: Full-time | R&D About Fujitsu R&D Fujitsu is a multibillion-dollar global corporation with approximately 124,000 professionals in multiple countries. Fujitsu has served as a trusted partner to the worldwide telecommunications industry for more than 85 years. More information about Fujitsu’s network products can be found at: https://www.fujitsu.com/us/products/network/ Job Summary: We are looking for a Senior Software Engineer – AI/ML with deep expertise in developing and deploying cloud-native machine learning solutions. This role demands strong proficiency in Python-based ML libraries, design of scalable microservices, and deep knowledge of NoSQL databases. The ideal candidate will have hands-on experience with ML algorithms, model performance tuning, model accuracy optimization, and proven delivery of AI applications in areas such as anomaly detection and time series forecasting. You will work closely with data scientists, cloud engineers, and product teams to build intelligent systems that operate at scale and deliver real-time insights into complex, high-volume data. Key Responsibilities: Design, develop, and deploy AI/ML microservices using Python in a cloud-native environment. Build scalable pipelines for training, tuning, and serving ML models in production. Integrate and manage NoSQL databases (e.g., MongoDB, ElasticSearch) for efficient storage and retrieval of unstructured or time-series data. Optimize model accuracy, latency, and throughput, including hyperparameter tuning, feature engineering, and profiling model performance. Lead the development of ML-based solutions for anomaly detection, time series forecasting, and predictive analytics. Collaborate with cross-functional teams to translate product requirements into ML-based features. Apply best practices in model versioning, A/B testing, and continuous training/validation. Ensure high standards of code quality, modularity, and observability in deployed services. Evaluate new tools, technologies, and frameworks for ML lifecycle management and monitoring. Required Skills: 5+ years of experience in backend software development using Python . Strong programming expertise in Python , with proficiency in ML libraries such as scikit-learn, TensorFlow, PyTorch , XGBoost, or LightGBM. Demonstrated experience in implementing anomaly detection algorithms and time series forecasting models (e.g., ARIMA, Prophet, LSTM). Good understanding of AI/ML algorithms like Random Forest, K-Means, Autoencoders, Graph Neural Networks (GNNs), and Louvain for anomaly detection, clustering, and time-series analysis. Experience in building and deploying cloud-native microservices (e.g., on AWS, Azure, GCP). Solid understanding of NoSQL databases like MongoDB, ElasticSearch storing ML data and time series. Messaging bus like Kafka or RabbitMQ Hands-on experience with model performance tuning, evaluation metrics, and real-world ML system optimization. Familiarity with ML lifecycle tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Understanding of containerization and orchestration (Docker, Kubernetes) for scalable deployment. Proficient in working with Git, CI/CD workflows, and Agile development methodologies. Experience with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions. Familiarity with Agile methodologies and ticketing systems (JIRA). Nice to Have: Experience applying ML to wireless network optimization. Familiarity with federated learning or edge AI techniques to enable distributed ML across radio/access nodes. Understanding of online learning or reinforcement learning for dynamic network adaptation and control. Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Senior Data Scientist Req number: R5797 Employment type: Full time Worksite flexibility: Hybrid Who we are CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise. Job Summary We’re searching for an experienced Senior Data Scientist who excels at statistical analysis, feature engineering, and end to end machine learning operations. Your primary mission will be to build and productionize demand forecasting models across thousands of SKUs, while owning the full model lifecycle—from data discovery through automated re training and performance monitoring. This is a Full-time and Hybrid position. Job Description What You’ll Do Advanced ML Algorithms: Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift). Apply automated hyperparameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME). Data Analysis & Feature Engineering: • Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies. Engineer predictive features from structured, semistructured, and unstructured data; manage feature stores (Feast). Ensure data quality through rigorous validation and automated checks. TimeSeries Forecasting (Demand): • Build hierarchical, intermittent, and multiseasonal forecasts for thousands of SKUs. Implement traditional (ARIMA, ETS, Prophet) and deeplearning (RNN/LSTM, TemporalFusion Transformer) approaches. Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias. MLOps & Model Lifecycle: • Establish model tracking & registry (MLflow, SageMaker Model Registry). Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions). Monitor data & concept drift; trigger retuning or rollback as needed. Statistical Analysis & Experimentation: • Design and analyze A/B tests, causal inference studies, and Bayesian experiments. Provide statisticallygrounded insights and recommendations to stakeholders. Collaboration & Leadership: Translate business objectives into datadriven solutions; present findings to exec & nontech audiences. Mentor junior data scientists, review code/notebooks, and champion best practices. What You'll Need M.S. in Statistics (preferred) or related field such as Applied Mathematics, Computer Science, Data Science. 5+ years building and deploying ML models in production. Expertlevel proficiency in Python (Pandas, NumPy, SciPy, scikitlearn), SQL, and Git. Demonstrated success delivering largescale demandforecasting or timeseries solutions. Handson experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining. Solid grounding in statistical inference, hypothesis testing, and experimental design. Experience in supplychain, retail, or manufacturing domains with highgranularity SKU data. Familiarity with distributed data frameworks (Spark, Dask) and cloud data warehouses (Big Query, Snowflake). Knowledge of deeplearning libraries (PyTorch, TensorFlow) and probabilistic programming (PyMC, Stan). Strong datavisualization skills (Plotly, Dash, Tableau) for storytelling and insight communication. Physical Demands This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc. Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor. Reasonable accommodation statement If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

lululemon is an innovative performance apparel company that specializes in providing high-quality products for yoga, running, training, and other athletic activities. Our focus lies in developing technical fabrics and functional designs to create products and experiences that support individuals in their journey of movement, growth, connection, and overall well-being. At lululemon, we attribute our success to our dedication to innovation, our commitment to our people, and the meaningful relationships we establish within the communities we serve. We are dedicated to driving positive change and fostering a healthier and more prosperous future. A key aspect of our mission involves cultivating an environment that is equitable, inclusive, and growth-oriented for all our team members. Our India Tech Hub is instrumental in enhancing our technological capabilities across various domains such as Product Systems, Merchandising and Planning, Digital Presence, distribution and logistics, and corporate systems. The team in India collaborates closely with our global team on projects of strategic significance. Joining the Content team at lululemon offers an exciting opportunity to contribute to a fast-paced environment that is constantly exploring new initiatives to support our rapidly expanding business. We are a team that embraces cutting-edge technology and is driven by a continuous pursuit of improvement. Innovation is at the core of our ethos, and we encourage each other to step out of our comfort zones and embrace new challenges. Professional and personal growth is paramount to us, and we believe in learning from failures to pave the way for a brighter future. We foster an environment where team members can freely share feedback and ideas, promoting ongoing organizational growth. Operating within an agile methodology, we collaborate with product teams across various functions and a core commerce platform team. At lululemon, we prioritize creating a culture of enjoyment and lightheartedness in our daily work routine. We recognize the strength in unity and celebrate the fact that we are more powerful as a team rather than as individuals. Responsibilities: - Develop Statistical/Machine Learning models/analysis for Merchandising and Planning Business problems - Play a key role in all stages of the Data science project life cycle - Collaborate with Product Management and Business teams to gain Business understanding and collect requirements - Identify necessary data sources and automate the collection process - Conduct pre-processing and exploratory data analysis - Evaluate and interpret results, presenting findings to stakeholders and business leaders - Collaborate with engineering and product development teams to deploy models into production systems when applicable Requirements and Skills: - Demonstrated experience in delivering technical solutions using Time Series/Machine Learning techniques - Proficient in applied Statistical skills, including familiarity with Statistical tests, distributions, etc. - Strong expertise in applied Machine Learning skills such as Time Series, Regression Analysis, Supervised and Unsupervised Learning - Proficient Programming Skills in Python and database query languages like SQL, with additional familiarity with Snowflake & Databricks being advantageous - Experience with time series forecasting techniques like ARIMA, Prophet, Deep AR - Familiarity with data visualization libraries such as Plotly, Business intelligence tools like PowerBI, Tableau - Excellent communication and presentation abilities - Previous experience in the Retail industry Responsibilities: - Identify valuable data sources and automate collection processes - Preprocess structured and unstructured data - Analyze large datasets to identify trends and patterns - Develop predictive models and machine-learning algorithms - Employ ensemble modeling techniques - Utilize data visualization methods to present information effectively - Propose actionable solutions and strategies to address business challenges - Collaborate with engineering and product development teams,

As a member of our team, you will be responsible for managing organizational strategy and operations through the design and statistical analysis of business initiatives and experiments. Your role will involve collaborating with business partners to understand and address their needs and issues effectively. Utilizing advanced knowledge of statistics and data mining techniques, such as predictive modeling and simulation, you will identify patterns and insights from business data. Additionally, you will be tasked with designing, developing, and evaluating statistical and predictive models to drive business solutions. In this position, you will act as the lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communication of findings and recommendations to management across various departments will be a crucial aspect of your role. Furthermore, you will support implementation efforts and lead and mentor the team working in the Data Competency Centre. To excel in this role, you should possess a Bachelor's degree in data science, computer science, electrical engineering, applied statistics, or physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence, or Machine Learning algorithm development. Alternatively, a Master's degree with 5+ years of relevant work experience or a PhD with 4+ years of relevant work experience in the aforementioned fields will also be considered. A working knowledge of budgets and financial statements is required. Key skills and competencies for this position include demonstrated experience in managing teams, coaching team members to drive results, proficiency in programming languages and statistical software tools (such as Python, SAS, R, JMP), relational databases (SQL server), and data analysis and visualization software (preferably PowerBI, SAS). You should also have experience with standard data science and machine learning packages, as well as machine learning model tradeoffs and computer vision models. Strong communication skills are essential to effectively collaborate with various business partners and communicate complex data relationships and statistical model results. Your essential responsibilities will involve statistical analysis and model development in collaboration with business partners, internal teams, and Enterprise Data Management. You will explore data using statistical techniques to answer business questions, build hypotheses, and identify research data attributes. Additionally, you will lead the development of experimental designs for business initiatives, apply advanced statistical techniques, build predictive models, and deploy computer vision models to meet business needs. Providing guidance and direction related to statistical analysis, as well as effectively communicating and delivering statistical and predictive model results to business partners, are critical aspects of this role. You will report to the Head of Automation Digital Transformation USA and will have direct reports. Some travel may be required for this position. This is a full-time role based in Plot No.A-1/1 SIPCOT Industrial Park, Sriperumbudur, Tamil Nadu, 602105, IN. If you believe you meet the qualifications and can excel in fulfilling the responsibilities outlined for this role, we encourage you to apply. All candidates receiving an offer of employment must successfully complete a background check and any other required tests. Job Identification: 1021960 Job Category: NPI-HSRT Integration Data Science Posting Date: 07/17/2025, 12:17 AM Job Schedule: Full time Work Schedule: Normal Shift New (PMT),

Job Title: Senior Data Scientist Location: Kolkata/Bangalore (Remote/Hybrid options available) Company: Inxite-out Job Overview: We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. This role will involve leading data science initiatives, developing advanced machine learning models, and providing actionable insights for business strategies. The ideal candidate will have a strong background in data science, statistical analysis, and business problem-solving, with a passion for delivering high-quality solutions. Key Responsibilities & Skills: Lead the development of advanced predictive and prescriptive models using machine learning, forecasting and other statistical methods Working knowledge of regression, classification, clustering, association algorithms and model optimization techniques Work closely with business stakeholders to understand requirements and translate them into data science solutions Design and implement end-to-end data science workflows, including data collection, preprocessing, feature engineering, model building, and evaluation Collaborate with cross-functional teams to deploy and integrate models into production environments Perform model validation, fine-tuning, and optimization to ensure accuracy and scalability Identify and investigate anomalies or unexpected behaviours in model outputs Build REST APIs using Fast/Flask, move models into production, ensure expected accuracies and throughput for the model Mentor and guide junior data scientists, providing technical expertise and leadership Qualifications: Bachelors or master’s in computer science, Statistics, Mathematics, Engineering, or a related field 4+ years of experience in data science or a similar analytical role, with a proven track record of delivering impactful projects Strong proficiency in python with experience in libraries like pandas, NumPy, Spacy, TensorFlow, Scikit-learn etc. Experience in working with cloud platforms (Azure), Databricks, PySpark Strong theoretical and practical knowledge of ML model development, hyper-parameter tuning, and production deployment Solid understanding of statistical analysis, data mining, feature engineering Strong problem-solving skills with the ability to think critically and adapt to complex business challenges Excellent communication skills with the ability to explain complex data-driven concepts to a non-technical audience Experience in leading and mentoring junior team members. Strong understanding of MLOps- lifecycle of a machine learning model Additional Skills (good to have): Knowledge of deep learning, CNN, MLP, OpenCV etc. Working knowledge of NLP/GenAI based solutions Experience working with SAP (S/4 HANA, BW) is a plus

Job Area: Engineering Group, Engineering Group > Hardware Engineering General Summary: As SoC Verification engineer, the candidate will be responsible to own SoC Interconnect DV (Connectivity matrix, Coherency, Clock gating, Performance etc) during the project work. Responsibilities Understand the design specification and implementation, define the verification scope, develop test plans, tests, and the verification infrastructure and verify the correctness of the design. Work alongside other members of the verification team to analyze, develop and execute verification test cases and able to provide relevant solution to issue. Collaborate with architects, designers, and pre and post silicon verification teams. Skillsets/Requirements B.E/B.Tech/M.E/M.Tech in Electronics with 7+ year experience in verification domain. Good understanding of Soc level verification testbench and flows. Prior work on NoC/Interconnects end to end verification with solid understanding on to Bus protocols, Coherency, Performance, Latency, clock gating etc. Working knowledge of Interconnect architecture and Bus protocols like AMBA - ACE/CHI/AXI. Solid hands-on working experience on System Verilog and UVM methodology. Expert in handling protocol BFM/VIP integration and traffic sequence development. Experience in coding assertions and functional coverage bins. Minimum Qualifications: Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience. OR Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 1+ year of Hardware Engineering or related work experience. OR PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Management Level: Ind & Func AI Decision Science Analyst Job Location: Bangalore / Gurgaon Must-have Skills: Life Sciences/Pharma/Healthcare projects and delivering successful outcomes, commercial, clinical, Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Good-to-have Skills: Proficiency in Programming languages such as R, Python, SQL, Spark, AWS, Azure, or Google Cloud for deploying and scaling language models, Data Visualization tools like Tableau, Power BI Job Summary We are seeking an experienced and visionary - Accenture S&C Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. Key Responsibilities Support delivery of small to medium-sized teams to deliver consulting projects for global clients. An opportunity to work on high-visibility projects with top Pharma clients around the globe. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Responsibilities may include strategy, implementation, process design, and change management for specific modules. Work with the team or as an Individual contributor on the project assigned which includes a variety of skills to be utilized from Data Engineering to Data Science Develop assets and methodologies, point-of-view, research, or white papers for use by the team and the larger community. Work on variety of projects in Data Modeling, Data Engineering, Data Visualization, Data Science etc., Acquire new skills that have utility across industry groups. Additional Information Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good communication, interpersonal, and presentation skills About Our Company | Accenture (do not remove the hyperlink) Qualification Experience: Proven experience (2+ years) in working on Life Sciences/Pharma/Healthcare projects and delivering successful outcomes. Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

Management Level: Ind & Func AI Decision Science Consultant Location: Gurgaon, Mumbai, Bangalore Must-have skills: Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, Time Series (ARMA/ARIMA), Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, PowerBI, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills: Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled Ind & Func AI Decision Science Consultant to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role offers opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstreams of small projects, overseeing the quality of deliverables for junior team members. Demonstrated ability to manage day-to-day interactions with client stakeholders. Practice Enablement Guide junior team members. Support development of the practice by driving innovations and initiatives. Develop thought leadership and disseminate information around current and emerging trends in Risk. Professional & Technical Skills: 2-6 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services/Risk Advisory with significant exposure to Credit Risk: PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior: Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk: Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML): AML Scenarios/Alerts, Network Analysis Operational Risk: AMA Modeling, Operational Risk Reporting Modeling Techniques: Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools: SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities. Industry Certifications:FRM, PRM, CFA preferred. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Qualification Experience: Minimum 2-6 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Management Level: Ind&Func AI Decision Science Consultant Job Location: Bangalore / Gurgaon Must-have Skills: Excellent understanding of Pharma data sets commercial, clinical, Leverage ones hands on experience of working across one or more of these areas such as real-world evidence data, Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Good-to-have Skills: Programming languages such as R, Python, SQL, Spark, AWS, Azure, or Google Cloud for deploying and scaling language models, Data Visualization tools like Tableau, Power BI. Job Summary This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Key Responsibilities An opportunity to work on high-visibility projects with top Pharma clients around the globe. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Provide Subject matter expertise in various sub-segments of the LS industry. Support delivery of small to medium-sized teams to deliver consulting projects for global clients. Responsibilities may include strategy, implementation, process design, and change management for specific modules. Work with the team or as an Individual contributor on the project assigned which includes a variety of skills to be utilized from Data Engineering to Data Science Develop assets and methodologies, point-of-view, research, or white papers for use by the team and the larger community. Acquire new skills that have utility across industry groups. Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Additional Information Proficient in Excel, MS Word, PowerPoint, etc. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good communication, interpersonal, and presentation skills About Our Company | Accenture (do not remove the hyperlink) Qualification Experience: Proven experience (4+ years) in working on Life Sciences/Pharma/Healthcare projects and delivering successful outcomes. Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

JR: R00229254 Experience: 11-15 Years Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field. ---- Job Title - S&C Global Network - AI - Healthcare Analytics - Senior Manager Management Level: 6-Senior Manager Location: Bangalore/Gurgaon Must-have skills: R,Phython,SQL,Spark,Tableau ,Power BI Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. WHATS IN IT FOR YOU An opportunity to work on high-visibility projects with top Pharma clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Lead proposals, and business development efforts and coordinate with other colleagues to cross-sell/ up-sell Life Sciences offerings to existing as well as potential clients. Lead client discussions, developing new industry Point of View (PoV), re-usable assets (tools) Collaborate closely with cross-functional teams including Data engineering, technology, and business stakeholders to identify opportunities for leveraging data to drive business solutions. Lead and manage teams to deliver transformative and innovative client projects. Guide teams on analytical and AI methods and approaches Manage client relationships to foster trust, deliver value, and build the Accenture brand Drive consulting practice innovation and thought leadership in your area of specialization Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Execute a transformational change plan aligned with the clients business strategy and context for change. Engage stakeholders in the change journey and build commitment to change. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. Proven experience in cross-sell/ up-sell Leverage ones hands-on experience of working across one or more of these areas such as real-world evidence data, R&D clinical data, and digital marketing data. Experience with handling Datasets like Komodo, RAVE, IQVIA, Truven, Optum, SHS, Specialty Pharmacy, PSP, etc. Experience in building and deployment of Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Excellent analytical and problem-solving skills, with a data-driven mindset. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good Client handling skills; able to demonstrate thought leadership & problem-solving skills. Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 11-15 Years Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

JOB RESPONSIBILITIES: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same

Invent, implement, and deploy state-of-the-art machine learning and/or specific domain industry algorithms and systems. Build prototypes and explore conceptually new solutions. Work collaboratively with science, engineering, and product teams to identify customer needs in order to create and implement solutions, promote innovation, and drive model implementations. Apply data science capabilities and research findings to create and implement solutions at scale. Responsible for developing new intelligence around core products and services through applied research on behalf of customers. Develop models, prototypes, and experiments that pave the way for innovative products and services. Build cloud services that work out-of-the-box for enterprises, e.g., decision support, anomaly detection, forecasting, and recommendations, natural language processing (NLP), Natural Language Understanding (NLU), Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Stay conversant on ethical problems in consideration of sciences. Drives and plans the implementation of company policy for achieving business goals. Define the bar for science practices and help teams achieve those goals. Identify and mitigate risks across the full set of systems, particularly at the intersection of business and engineering. Innovate AI and ML-powered solutions (rich APIs, ML models, and end-to-end services) with strategic ISVs and customers. Develop deep product intuition to influence future product roadmaps and drive decision-making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward-looking research both internally and with academic institutions globally. Hire and mentor across the organization. Play an active role in team planning, review, and retrospective events. Ensure experiments are ready for hand-off to Software Developers to ship into production. May perform other duties as assigned. Career Level - IC5 As a world leader in cloud solutions, Oracle uses tomorrow's technology to tackle today's challenges. We've partnered with industry leaders in almost every sector and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That's why we're committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States.,

You will be working at ClearTrail, where the focus is on developing solutions to empower organizations dedicated to ensuring the safety of their people, places, and communities. With over 23 years of experience, ClearTrail has been a trusted partner for law enforcement and federal agencies worldwide in safeguarding nations and enriching lives. As part of the team, you will contribute to the future of intelligence gathering by creating artificial intelligence and machine learning-based lawful interception and communication analytics solutions to address some of the world's most challenging problems. Your role will involve developing and training machine learning models that leverage drone, satellite, and real-time video data for complex visual understanding tasks. You should have a minimum of 10-12 years of relevant experience for this position. Key responsibilities of the role include: - Building machine learning and deep learning models for image and video classification, segmentation, and spatiotemporal analysis. - Developing fusion methods to align and combine data from satellite, drone, and ground footage. - Applying advanced techniques such as multi-scale learning, temporal modeling (e.g., 3D CNNs, transformers), and sensor fusion. - Conducting model evaluation and optimization across various data sources. Essential skills for this role include: - Strong proficiency in Python coding and data manipulation using libraries such as NumPy, Pandas, and SciPy. - Expertise in vision/model libraries like MMDetection, Detectron2, and OpenCV. - Deep learning experience with PyTorch, TensorFlow, and video models such as TimeSformer, SlowFast, I3D, and Yolo. - Knowledge of satellite/drone geospatial fusion, GPS/IMU metadata, and scene alignment. - Familiarity with time series analysis, motion tracking, and optical flow using tools like RAFT and FlowNet. - Understanding of remote sensing libraries such as Rasterio, GDAL, GeoPandas, and xarray. If you are passionate about leveraging machine learning and artificial intelligence to address complex challenges in intelligence gathering, this role at ClearTrail offers an exciting opportunity to make a meaningful impact.,

Overview We are PepsiCo We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Purpose . For more information on PepsiCo and the opportunities it holds, visitwww.pepsico.com. Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines. PepsiCo Data Analytics & AI Overview With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCos leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AIProducts. And will support pre-engagement activities as requested and validated by the prioritization framework of DA&AI. Data ScientistHyderabad and Gurugram You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Active contributor to code & development in projects and services Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption. Partner with ML engineers working on industrialization. Communicate with business stakeholders in the process of service design, training and knowledge transfer. Support large-scale experimentation and build data-driven models. Refine requirements into modelling problems. Influence product teams through data-based recommendations. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create reusable packages or libraries. Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Leverage big data technologies to help process data and build scaled data pipelines (batch to real time) Implement end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines Automate ML models deployments Qualifications BE/B.Tech in Computer Science, Maths, technical fields. Overall 5+ years of experience working as a Data Scientist. 4+ years experience building solutions in the commercial or in the supply chain space. 4+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus. Fluent in SQL syntaxis. 4+ years experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. 4+ years experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development. Skills, Abilities, Knowledge Data Science Hands on experience and strong knowledge of building machine learning models supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is a plus Programming Skills Hands-on experience in statistical programming languages like Python , Pyspark and database query languages likeSQL Statistics Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Cloud (Azure) Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pigis an added advantage Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool. Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities Experience with Agile methodology for team work and analytics product creation.

You will be responsible for developing and training machine learning models that leverage drone, satellite, and real-time video data to tackle complex visual understanding tasks. Your primary focus will be on building ML/DL models for image and video classification, segmentation, and spatiotemporal analysis. Additionally, you will be tasked with developing fusion methods that align and merge data from satellite, drone, and ground footage sources. To excel in this role, you must have a minimum of 10-12 years of relevant experience. You should possess strong Python coding skills along with expertise in data manipulation using libraries such as NumPy, Pandas, and SciPy. Proficiency in vision/model libraries such as MMDetection, Detectron2, and OpenCV is essential. Moreover, you must have hands-on experience in deep learning frameworks like PyTorch and TensorFlow, particularly in developing video models with TimeSformer, SlowFast, I3D, Yolo, among others. Your expertise should extend to satellite/drone geospatial fusion, GPS/IMU metadata, and scene alignment. Familiarity with time series analysis, motion tracking, and optical flow techniques (e.g., RAFT, FlowNet) is beneficial. In addition, knowledge of remote sensing libraries like Rasterio, GDAL, GeoPandas, and xarray will be advantageous for this role. Your responsibilities will also include model evaluation and optimization across various data sources, ensuring the delivery of high-quality solutions that contribute to the future of intelligence gathering.,

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up . Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy Data & Analytics Behind one of the worlds best loved brands is a uniquely capable and brilliant team of data scientists, engineers and analysts. The Target Data & Analytics team creates the tools and data products to sustainably educate and enable our business partners to make great data-based decisions at Target. We help develop the technology that personalizes the guest experience, from product recommendations to relevant ad content. Were also the source of the data and analytics behind Targets Internet of Things (iOT) applications, fraud detection, Supply Chain optimization and demand forecasting. We play a key role in identifying the test-and-measure or A/B test opportunities that continuously help Target improve the guest experience, whether they love to shop in stores or at Target.com. About you: Four-year degree or equivalent experience 3+ year as a Data Analyst with strong academic performance in a quantitative field; or strong equivalent experience [add any specific analyst experience needed here] Advanced SQL experience writing complex queries Intermediately accomplished with Python or R Solid problem solving, analytical skills, data curiosity, data mining, Data creation and consolidation Support conclusions with a clear, understandable story that leverages descriptive statistics, basic inferential statistics, and data visualizations Willingness to ask questions about business objectives and the measurement needs for a project workstream, and be able to measure objectives & key results Excellent communication skills with the ability to speak to both business and technical teams, and translate ideas between them Knowledge of AB Testing methods, time series, S&OP planning, Forecasting models including statistical analysis Experience in analytics tools such asSQL, Excel, Hadoop, Hive, Spark, Python, R, Domo, Adobe Analytics (or Google Analytics) and/or equivalent technologies Useful Links- Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid overview A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on Every Scientist on Targets Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Targets culture and apply retail domain knowledge. Position Overview: As a Senior Data Scientist, you will be involved in end-to-end development of Ad-Tech products and capabilities that fulfil strategic priorities and power growth of Roundel, Targets Retail media business. You will leverage understanding of data and algorithms to build prototypes and run experiments to evaluate them against given specifications. As you follow agile processes, you will implement and deploy a scalable data science solution by using MLOps best practices across model development life cycle. You will collaborate with product and business partners to seek feedback on effectiveness of solution and identify future opportunities for enhancements. You will work with your peers to create a well-maintainable & tested codebase with relevant documentation. The exciting part of retail and mediaIts always changing! Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs. About You: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience 3+ years of professional experience or equivalent industry experience Good knowledge and experience developing optimization, simulation and statistical models Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches, where required Strong hands-on programming skills in Python, SQL, Spark, Hadoop/Hive . Good working knowledge of mathematical and statistical concepts, MILP, algorithms and computational complexity Passion for solving interesting and relevant real-world problems using a data science approach Experience in implementing advanced statistical techniques like r egression, clustering, PCA, forecasting (time series) etc. Able to produce reasonable documents/narrative suggesting actionable insights Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs and narratives Self-driven and results oriented; able to meet tight timelines Strong team player with ability to collaborate effectively across geographies/time zones Know More here: Life at Target - https://india.target.com/ Benefits - https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up . Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid overview A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on Every Scientist on Targets Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Targets culture and apply retail domain knowledge. About the role As aLead Data Scientist, youll influence by interacting with the Data Sciences team, Product teams, Scientist/Engineer individual contributors from other pillars, and business partners. You will perform within the scale and scope of your role by defining solutions and beginning to identify problems to solve and contribute to Data Sciences and Targets culture by modeling and contributing to the culture. Youll get the opportunity to use your expertise in one or more of the following areasmachine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, Deep Learning, Natural Language processing or computer vision. We will look to you to own design and implementation of an algorithmic solution (e.g., recommendation or forecasting algorithm), including data understanding, feature engineering, model development, validation and testing, and deployment to a production environment. Youll drive development of problem statements that capture the business considerations, define metrics/measurement to validate model performance, and drive feasibility study with data requirements and potential solutions approaches to be considered. Youll evaluate tradeoffs of simple vs complex models/solutions in determining the right technique to employ for a business problem and develop and maintain a nuanced understanding of the data generated by the business, including fundamental limitations of the data. Youll leverage your proficiency in one or more approved programming languages (Java, Scala, Python, R), and ensure foundational programming principles in developing code (best practices, writes unit tests, code organization, basics of CI/CD etc.) are followed in developing the teams products/models. Youll not only stitch together basic data pipelines for a given problem and own design and implementation of individual components within Data Science/Tech applications, but also articulate the technical strategy, value of technology, and impact on the business. As you do so, youll collaborate with engineers, scientists, and business partners/product owners to create algorithmic solutions that are performant and integrated into applications. Well look to you to mentor and provide technical support within a team, including mentoring junior team members, and present your work and your teams work to business partners and other Data Sciences teams. With a deeper understanding of your functional area of responsibility, youll support agile ceremonies, collaborate with peers across multiple products, communicate and collaborate with business partners, and demonstrate an understanding of areas outside your scope of responsibility. The exciting part of retailIts always changing! Core responsibilities of this job are described within this job description.Job duties may change at any time due to business needs. About you: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) and 6+ years of professional experience or equivalent industry experience Masters degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) Good knowledge and experience developing optimization, simulation, and statistical models Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory Good working knowledge of mathematical and statistical concepts, MILP, algorithms, and computational complexity Passion for solving interesting and relevant real-world problems using a data science approach Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series) etc. Able to produce reasonable documents/narrative suggesting actionable insights Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented; able to meet tight timelines Strong team player with ability to collaborate effectively across geographies/time zones Know More About us here: Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging