Sr Data Scientist-Pricing & Clearance

About Us

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 hasn’t 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 Target’s global team and has more than 5,000+ team members supporting the company’s global strategy and operations.

Pyramid Overview

A role with Target Data Science & Engineering offers the opportunity to develop cutting-edge AI, Machine Learning, and Optimization solutions that leverage data at scale to drive intelligent, automated business decisions. Our teams work at the intersection of advanced analytics, predictive modeling, Generative AI, and decision intelligence to solve complex retail challenges and deliver meaningful business impact.

Team Overview

The Pricing and Clearance Data Science team develops advanced AI/ML and optimization solutions that enable smarter, data-driven pricing and markdown decisions across Target. The team focuses on demand forecasting, price elasticity , intelligent optimization, simulation, and scenario planning to improve financial outcomes and operational efficiency. Working at the intersection of Machine Learning, Generative AI, Agentic AI , Optimization, and Retail Science, the team builds scalable, production-ready solutions that enhance decision-making, automate complex workflows, and drive continuous innovation across Target's retail ecosystem.

Role Overview

As a Senior Data Scientist in Merchandising , you will help shape how Target makes pricing and clearance decisions by turning complex retail challenges into measurable business impact. You will build scalable AI/ML solutions that improve recommendation quality, decision efficiency, and financial outcomes.

You will collaborate with Data Scientists, Product Managers, Engineers, Analysts, Merchandising partners, and business stakeholders to translate complex retail challenges into scalable, production-ready AI/ML solutions.

This role is ideal for someone with strong foundations in Machine Learning, forecasting, statistical modeling, and applied optimization , along with hands-on experience in Generative AI, LLM applications, or Agentic AI . You will have opportunities to work on AI-powered explainability, automated model evaluation, intelligent decision-support systems, and next-generation retail optimization solutions.

Key Responsibilities

• 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.

About You

• 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.

Must-Have Skills

• 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 / Good-to-Have Skills

• 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.

Know More About Us here:

• Life at Target - https://india.target.com/
• Benefits - https://india.target.com/life-at-target/workplace/benefits

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