About The Position

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Every scientist on Target’s Data Sciences team can expect to do modeling and data science, develop software with highly performant code, elevate Target’s culture, and apply retail domain knowledge. As a Lead Data Scientist - Recommendations, you will provide technical leadership for the machine learning systems that power Target's digital recommendations and personalization experiences. Working closely with data scientists, engineers, product managers, and business stakeholders, you will identify opportunities to improve guest experiences through recommendation, retrieval, ranking, and personalization solutions at a massive scale. You will lead the design, development, evaluation, and deployment of machine learning models that influence how millions of guests discover products across Target's digital experiences. Leveraging expertise in machine learning, deep learning, experimentation, and optimization, you will translate ambiguous business challenges into scalable algorithmic solutions that drive measurable guest and business impact. You will be responsible for driving projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence and long-term maintainability. You will help shape the technical direction of Target's recommendation capabilities, establishing best practices for model development, evaluation, and measurement while influencing decisions across product, engineering, and data science teams. Beyond delivering solutions, you will mentor and develop other scientists, help raise the technical bar across the organization, and contribute to the growth of Target's data science community through collaboration, thought leadership, and the adoption of emerging machine learning techniques and technologies. Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

Requirements

  • PhD or MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, or a related quantitative field with 2+ years of industry experience
  • 5+ years of experience developing machine learning solutions scaling recommendation, personalization, ranking, retrieval, or search machine learning systems
  • Experience with reinforcement learning and/or contextual bandit design, implementation, and evaluation
  • Experience leading the development, evaluation, and deployment of machine learning solutions and partnering with engineering teams to deliver scalable production systems
  • Strong programming skills in Python and SQL; experience with deep learning frameworks such as PyTorch or JAX
  • Experience working with large-scale data processing and analytics platforms such as Spark or equivalent
  • Deep understanding of machine learning, deep learning, optimization, statistics, probability, and experimental design
  • Experience designing, analyzing, and interpreting online experiments and using results to inform product and business decisions
  • Demonstrated ability to translate ambiguous business challenges into scalable machine learning solutions
  • Demonstrated ability to influence technical direction and drive alignment across product, engineering, and business stakeholders
  • Experience leveraging modern AI and generative AI tools to accelerate development, experimentation, and model delivery
  • Excellent communication skills with the ability to clearly communicate complex technical concepts to both technical and non-technical audiences
  • Strong software engineering fundamentals, including testing, code reviews, documentation, and maintainable system design

Responsibilities

  • Provide technical leadership for the machine learning systems that power Target's digital recommendations and personalization experiences.
  • Identify opportunities to improve guest experiences through recommendation, retrieval, ranking, and personalization solutions at a massive scale.
  • Lead the design, development, evaluation, and deployment of machine learning models that influence how millions of guests discover products across Target's digital experiences.
  • Translate ambiguous business challenges into scalable algorithmic solutions that drive measurable guest and business impact.
  • Drive projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence and long-term maintainability.
  • Help shape the technical direction of Target's recommendation capabilities, establishing best practices for model development, evaluation, and measurement.
  • Influence decisions across product, engineering, and data science teams.
  • Mentor and develop other scientists.
  • Help raise the technical bar across the organization.
  • Contribute to the growth of Target's data science community through collaboration, thought leadership, and the adoption of emerging machine learning techniques and technologies.

Benefits

  • Comprehensive health benefits and programs, which may include medical, vision, dental, life insurance
  • 401(k)
  • Employee discount
  • Short term disability
  • Long term disability
  • Paid sick leave
  • Paid national holidays
  • Paid vacation
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service