Senior Data Scientist – Promo Optimisation

Role Overview

A Senior Data Scientist will work with Target’s rich data ecosystem and partner with product, engineering, analytics, and business teams to create scalable decisioning systems that deliver measurable business and guest impact.

What You Will Do

The role involves designing, developing, deploying, and improving scalable data science solutions for retail promotion optimization, collaborating with product managers, engineers, data scientists, analysts, and business partners, and mentoring junior team members.

Why It Might Be a Fit

The ideal candidate will have a strong foundation in supervised and unsupervised learning, probability, statistics, experimental design, model evaluation, and data analysis, with experience applying machine learning techniques to solve business problems in retail, e-commerce, Marketing, personalization, promotions, pricing, supply chain, advertising, or customer decisioning.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, Operations Research, Industrial Engineering, Economics, Physics, Applied Sciences, or a related quantitative field.
• 4+ years of relevant experience in data science, applied machine learning, operations research, optimization, AI engineering, or advanced analytics.
• Hands-on experience applying machine learning techniques to solve business problems, preferably in retail, e-commerce, Marketing, personalization, promotions, pricing, supply chain, advertising, or customer decisioning.
• Strong foundation in supervised and unsupervised learning, probability, statistics, experimental design, model evaluation, and data analysis.
• Experience with one or more areas of operations research, such as linear programming, mixed-integer programming, constrained optimization, simulation, stochastic processes, heuristic optimization, or decision science.
• Experience building and deploying models or algorithmic systems that create measurable business impact in production environments.
• Strong programming skills in Python and SQL, with experience working with large-scale data platforms such as Spark, Hadoop, Hive, or cloud-based distributed data environments.
• Experience with ML frameworks and libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, OR-Tools, Pyomo, Gurobi, CPLEX, or similar tools.
• Working knowledge of MLOps and production ML practices, including model versioning, automated pipelines, testing, monitoring, reproducibility, CI/CD, observability, and model governance.
• Ability to clean, transform, join, and analyze large datasets and convert complex data into actionable insights and production-ready features.
• Strong software engineering discipline, including modular code design, testing, code reviews, documentation, source control, and collaborative development practices.
• Ability to balance scientific rigor with practical business delivery, making thoughtful trade-offs between model complexity, explainability, scalability, and operational feasibility.
• Strong analytical thinking, structured problem-solving, and data visualization skills.
• Ability to communicate complex technical concepts clearly to technical and non-technical audiences.
• Self-driven, curious, and results-oriented, with the ability to operate in ambiguous problem spaces and deliver against tight timelines.
• Strong collaboration skills and the ability to work effectively across teams, functions, geographies, and time zones.

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• 401(k) plan
• Paid time off
• Paid holidays
• Flexible work arrangements
• Professional development opportunities
• Wellness programs
• Employee assistance program
• Disability insurance
• Life insurance
• Travel insurance
• Accidental death and dismemberment insurance