Lead Data Scientist - Recommendations (applied ML, Reinforcement Learning, Contextual Bandit Design)

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

Benefits offered by this job

Health benefits

401(k) matching

Paid time off

Employee discount

Short/Long term disability

Paid national holidays

Paid vacation

Job summary

Target is seeking a Lead Data Scientist - Recommendations to provide technical leadership for scalable ML systems powering Target's digital recommendations. You will collaborate with data scientists, engineers, product managers, and business stakeholders to enhance guest experiences through ranking, retrieval and personalization across Target's digital touchpoints.

You will mentor other scientists, drive projects from problem definition to production deployment, and help set best practices for

Qualifications

• 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.
• 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.

Responsibilities

• Lead the design, development, evaluation, and deployment of machine learning models that power Target's digital recommendations and personalization experiences.
• Mentor and develop other scientists, collaborate with data scientists, engineers, product managers, and business stakeholders.
• Drive projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence.
• Help shape the technical direction of Target's recommendation capabilities and establish best practices for model development, evaluation, and measurement.

Skills

Python

SQL

Communication

Experiment design

Team leadership

Education

MS/PhD in CS/ML/Statistics/Applied Math/OR

Tools

PyTorch

JAX

Spark

Job description

The pay range is $132,000.00 - $238,000.00

Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits .

JOIN TARGET AS A LEAD DATA SCIENTIST - RECOMMENDATIONS (RecSys)

About Us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here .

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.

About you:

• 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

This position may be considered fo