Lead Data Scientist, Recommendations — Remote

Target; Minneapolis (MN); Hybrid; USD 132,000 - 238,000; Full time

Job summary

Target is seeking a Lead Data Scientist – Recommendations to steer machine learning systems powering Target's digital recommendations. You will collaborate with data scientists, engineers, product managers and business stakeholders to improve guest experiences through ranking, retrieval and personalization at a massive scale.

You will design, deploy and evaluate models, mentor peers, and influence technical direction while balancing innovation with operational excellence and maintainability.

Qualifications

• PhD or MS in CS/ML/statistics or related field.
• 5+ years building ML solutions for recommendations, personalization, ranking or search.
• Experience with reinforcement learning and contextual bandit design.
• Experience leading ML development and deployment with engineering teams.
• Strong Python/SQL and PyTorch or JAX experience.
• Experience with large-scale data processing platforms such as Spark.

Responsibilities

• Lead design, development, evaluation and deployment of ML models for recommendations at scale.
• Mentor and develop other scientists, raise technical standards.
• Collaborate with product, engineering and business stakeholders to drive impact.
• Translate business problems into scalable ML solutions and measure results.

Skills

Python

SQL

Communication

Experimentation

Reinforcement learning

Education

PhD or MS in CS/ML/Statistics

Tools

PyTorch

JAX

Spark

Git

Docker

Job description

Target is seeking a Lead Data Scientist – Recommendations to steer machine learning systems powering Target's digital recommendations. You will collaborate with data scientists, engineers, product managers and business stakeholders to improve guest experiences through ranking, retrieval and personalization at a massive scale.

You will design, deploy and evaluate models, mentor peers, and influence technical direction while balancing innovation with operational excellence and maintainability.