Sr Data Scientist- Space Presentation

Role Overview As a Senior Data Scientist in Merchandising , you will help build and improve data science ML and Optimization models that power Target's Planogram capabilities. The primary focus of this role will be Sales Forecasting and elasticity models with optimization-based presentation recommendations. You will partner with Data Scientists, Product Managers, Engineers, Analysts, Merchandising partners, and business stakeholders to translate complex problems into scalable modelling solutions. This role is ideal for someone with strong foundations in machine learning, statistical modeling, forecasting, and applied optimization, with interest in solving high-impact retail problems at scale. Experience with Generative AI, LLMs, RAG, or AI agents is a plus as the team explores AI-enabled measurement, explainability, monitoring, and decision-support workflows. Key Responsibilities Develop, validate, and improve forecasting and elasticity models (using Regressions) that estimate Sales which is used as input for facings recommendations on Planogram. Account for multiple variables present in forecasting and separate impact of target variable on Sales.(Vif, multicollinearity) Use optimization to recommend optimal item placements on POG such that expense to service POG’s is lower and all item facings which are recommended fit on the POG (constrained Linear programming including the use of Fuzzy logic constraints) Create Item groups/segments to measure POG Performance and recommend changes using segmentation and similarity measures Scale and deploy solution to production environments Create measurement frameworks to evaluate model performance Partner with business and product teams to understand strategy, define success metrics, and translate requirements into model design. Work with large-scale retail data including sales, presentation history, item attributes, inventory, store and market attributes, and guest demand signals. Conduct deep-dive analyses to diagnose model performance, elasticity behavior, underperforming recommendations, outliers, sparse data, and category-specific pricing patterns. Support experimentation and measurement design, including A/B tests, market tests, incrementality measurement, control/test methodology, and model impact assessment. Collaborate with ML Engineers and Software Engineers to productionize models, automate pipelines, improve reliability, and integrate outputs into business-facing workflows. Monitor model performance over time, identify drift or degradation, and recommend improvements to maintain model quality and business impact. Communicate model logic, assumptions, trade-offs, risks, and recommendations clearly to technical and non-technical stakeholders. Contribute to model explainability and adoption by helping business partners understand why recommendations are generated. Explore Gen AI, LLMs, RAG, and agents for pricing use cases such as explainability, measurement automation, performance monitoring, and recommendation efficiency. About You Bachelor’s, Master’s, or Ph D in Data Science, Statistics, Economics, Mathematics, Operations Research, Computer Science, Engineering, or a related quantitative field. 4+ years of relevant experience in data science, applied machine learning, , forecasting, optimization, retail domain knowledge, GCP , Big Data. Strong hands-on experience building and validating machine learning or statistical models in a business setting. Experience within Merchandising on elasticity modeling, demand modeling and forecasting. Strong understanding of statistical concepts, model evaluation, feature engineering, regularization, cross-validation, uncertainty, and model interpretability. Experience with Optimization such as constrained optimization, linear programming, mixed-integer programming, Experience with experimentation and measurement. Ability to work on Big Data Ability to scale solutions to production enviironments Strong programming skills in Python and SQL, with experience working on large datasets using Spark, Py Spark, Hive, Hadoop, or similar platforms. Ability to analyze complex data, diagnose model issues, and convert findings into actionable recommendations. Ability to work in ambiguous problem spaces, structure analytical approaches, and deliver high-quality outcomes against business timelines. Strong communication and collaboration skills, with the ability to partner across Data Science, Product, Engineering, Analytics, Merchandising, and business teams. Must-Have Skills Strong experience in Python, SQL, and large-scale data analysis. Hands-on experience with machine learning, statistical modelling, and model validation. Experience with demand forecasting, elasticity modelling and optimization. Strong understanding of feature engineering, backtesting, model evaluation, and performance diagnostics. Experience working with large-scale structured data using Spark, Py Spark, Hive, Hadoop, or similar platforms. Basic to intermediate experience with optimization methods, simulations, or constraint-based decisioning. Ability to translate business problems into analytical and modeling solutions. Strong documentation, storytelling, and stakeholder communication skills. Preferred / Good-to-Have Skills Experience in retail, merchandising. Experience with scalable model pipelines, automated retraining, model monitoring, explainability, and MLOps practices. Experience with market testing, synthetic controls, double-delta measurement, or causal impact frameworks. Exposure to Generative AI and LLM applications, including prompt engineering, RAG, embeddings, vector databases, evaluation, and workflow automation. Exposure to agentic AI systems, including AI agents, tool use, Lang Graph, Lang Chain, Llama Index, and human-in-the-loop workflows. Experience building explainability, monitoring, or decision-support tools for business users. Experience with cloud platforms, APIs, containerization, workflow orchestration, MLflow, Airflow, Docker, Kubernetes, or similar tools. 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 Target is one of the world’s most recognized brands and one of America’s leading retailers. We make Target our guests’ preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver. Target is committed to responsible corporate citizenship, ethical business practices, environmental stewardship and generous community support. Since 1946, we have given 5 percent of our profits back to our communities. Our goal is to work as one team to fulfill our unique brand promise to our guests, wherever and whenever they choose to shop. We'll contact you if you're selected for next steps. In the meantime, follow us at A Bullseye View for the latest news. Our Benefits We care about and invest in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.