Sr Data Scientist-Pricing & Clearance
Target · Posted Nov 3
General merchandise, apparel, grocery, and home goods retail services
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About the role
Target Data Science & Engineering develops AI, Machine Learning, and Optimization solutions that leverage data at scale to drive automated business decisions. The Pricing and Clearance Data Science team focuses on demand forecasting, price elasticity, intelligent optimization, simulation, and scenario planning at the intersection of Machine Learning, Generative AI, Agentic AI, and Retail Science. This senior role builds scalable, production-ready AI/ML solutions for pricing and markdown decisions, including forecasting and elasticity models, GenAI/agentic explainability and diagnostics, and cloud-deployed decision-support systems.
What you will do
- Design and develop advanced AI/ML solutions for retail demand forecasting, price elasticity modeling, markdown optimization, and intelligent pricing decisions.
- Leverage advanced Machine Learning techniques, including ensemble learning, gradient boosting, deep learning, and time-series forecasting, to capture complex demand patterns and pricing sensitivities.
- Develop Generative AI and Agentic AI solutions leveraging LLMs, RAG, tool calling, and multi-agent architectures for automated model diagnostics, explainability, and intelligent decision-making.
- Build simulation, scenario planning, and what-if analysis frameworks to evaluate alternative pricing strategies, forecast outcomes, business trade-offs, and potential financial impact.
- Develop intelligent decision optimization frameworks combining predictive modeling, mathematical optimization, and business constraints to recommend optimal pricing and markdown strategies at scale.
- Design robust model evaluation and experimentation frameworks using forecast accuracy, bias analysis, A/B testing, causal inference, and counterfactual measurement to quantify business impact.
- Work with large-scale retail data to identify demand patterns, diagnose model performance, and continuously improve recommendation quality.
- Build automated model monitoring and evaluation capabilities to identify performance degradation, data quality issues, and emerging business trends.
- Partner with business, product, and engineering teams to translate complex retail challenges into scalable AI-powered solutions.
- Collaborate with engineering teams to productionize models, automate pipelines, and integrate AI/ML solutions into enterprise decision-making workflows.
- Drive innovation by exploring emerging AI technologies, modern forecasting architectures, and autonomous decision intelligence capabilities.
- Develop, deploy, and operationalize Machine Learning solutions on cloud platforms such as Google Cloud Vertex AI (preferred), AWS, or Microsoft Azure.
Skills used in this role
What the employer is looking for
- Bachelor's, Master's, or PhD 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, or AI-driven solutions.
- Strong foundation in Machine Learning, statistical analysis, predictive modeling, model validation, and mathematical optimization.
- Hands-on experience with Generative AI, LLM applications, or Agentic AI frameworks.
- Experience with simulation techniques, scenario planning, and data-driven decision-support systems.
- Strong programming expertise in Python and SQL, with experience processing large-scale datasets using distributed computing frameworks.
- Experience developing scalable ML solutions and familiarity with cloud platforms, preferably GCP and Vertex AI.
- Strong analytical thinking, problem-solving abilities, and the ability to navigate ambiguous business challenges.
- Excellent communication and collaboration skills, with the ability to partner across technical and business teams.
- Python, SQL, and Big Data technologies such as Spark, PySpark, Hive, or Hadoop.
- Machine Learning and Forecasting: Predictive modeling, feature engineering, model validation, and performance evaluation.
- Generative AI and Agentic AI: Hands-on experience with LLMs, prompt engineering, RAG, AI agents, or tool-calling frameworks.
- Optimization: Understanding of mathematical optimization, constraint-based decision-making, and optimization algorithms.
- Simulation and Scenario Planning: Experience with what-if analysis, simulation techniques, or scenario-based decision modeling.
- Statistical Experimentation: A/B testing, hypothesis testing, and model impact measurement.
- Production ML: Experience building scalable ML solutions and familiarity with cloud-based deployment.
- Strong problem-solving, stakeholder communication, and analytical storytelling skills.
Preferred qualifications
- Experience in retail, merchandising, pricing, demand forecasting, or inventory optimization.
- Experience with Google Cloud Platform (GCP), particularly Vertex AI, or comparable AWS/Azure ML services.
- Familiarity with LangGraph, LangChain, LlamaIndex, vector databases, embeddings, and multi-agent orchestration.
- Experience with causal inference, Difference-in-Differences, synthetic controls, or incrementality measurement.
- Exposure to advanced optimization, stochastic simulation, or decision intelligence frameworks.
- Knowledge of MLOps, automated pipelines, model monitoring, Docker, Kubernetes, MLflow, or workflow orchestration tools.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Target
Target Corporation operates an extensive chain of general merchandise and discount retail department stores across the United States. The company provides a broad assortment of owned and national brand products, including apparel, electronics, beauty items, groceries, and home goods. Through its physical stores and digital platforms, Target focuses on delivering style, design, and value to help consumers discover the joy of everyday life.
- Industry
- Retail
- Company size
- 415000+ employees
- Founded
- 1902
- Location
- Minneapolis, Minnesota, USA
- Funding stage
- Public Company
Leadership
Chief Executive Officer
Executive Chair of the Board
Jim Lee
Executive Vice President and Chief Financial Officer
Prat Vemana
Executive Vice President and Chief Information and Product Officer
Mark Weinstein
Executive Vice President and Chief Marketing and Guest Experience Officer
Recent coverage
Home Page News
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AP News
Target regains its footing under a new CEO and raises expectations for 20262026-08-19
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Target Unveils Multi-Year Strategy Under CEO Michael Fiddelke to Accelerate Growth2026-03-03