Sr Data Scientist- Promo Optimisation

Target is hiring a Sr Data Scientist- Promo Optimisation in Bangalore.

Responsibilities

• Develop a deep understanding of Target’s promotion ecosystem, guest behavior, Marketing objectives, offer funding, incremental sales, redemption, and business constraints.

• Translate business problems in promotion personalization and offer optimization into data science, machine learning, causal inference, simulation, and mathematical optimization problems.

• Analyze large-scale structured and unstructured datasets to identify guest, item, offer, channel, and campaign patterns that can improve model performance and business outcomes.

• Design, build, and evaluate machine learning models for segmentation, propensity, redemption prediction, incremental response, offer ranking, personalization, and guest-level decisioning.

• Develop optimization-based solutions using linear programming, mixed-integer programming, constrained optimization, stochastic optimization, simulation, and heuristic approaches to allocate offers under business, budget, inventory, guest experience, and operational constraints.

• Apply experimentation, causal inference, uplift modeling, and statistical measurement techniques to estimate incremental impact, validate model decisions, and guide business trade-offs.

• Build and productionalize scalable data science pipelines using Python, SQL, Spark, Hadoop/Hive, and modern ML frameworks.

• Partner with engineering teams to deploy models and decisioning modules into production systems with strong attention to reliability, scalability, latency, observability, and maintainability.

• Contribute to AI engineering and MLOps capabilities, including feature pipelines, model versioning, automated training, batch and real-time scoring, model monitoring, drift detection, alerting, retraining workflows, and performance dashboards.

• Use Generative AI and advanced AI techniques where appropriate to accelerate experimentation, improve decision support, enhance model development workflows, or create scalable business-facing tools.

• Develop and maintain simulation frameworks to test promotion strategies, compare scenarios, evaluate business constraints, and understand downstream impact before production rollout.

• Troubleshoot issues in data pipelines, model outputs, optimization results, and production systems; identify root causes and implement durable fixes.

• Create clear documentation, model evaluation summaries, experiment readouts, and technical narratives that help stakeholders understand model behavior, trade-offs, risks, and business impact.

• Collaborate across geographies and time zones with data scientists, engineers, product managers, analysts, and business partners.

• Mentor junior data scientists and analysts by reviewing approaches, improving code quality, strengthening analytical rigor, and helping them connect data science methods to business outcomes.

• Stay current with developments in machine learning, operations research, Generative AI, experimentation, and MLOps, and apply relevant techniques to Target’s retail challenges.

About Target

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 while striving to make a meaningful and positive impact for our guests, team members, and communities. Becoming a Target team member means joining a community that values diverse voices, encourages authenticity, and lifts each other up. At Target, we have a timeless purpose and a proven strateg