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

The pay range is $132000.00 - $238000.00

Pay is based on several factors which vary based on include labor markets and in some instancesmay include education work experience and 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 benefits for eligible team members include 401(k) employee discount short term disability long term disability paid sick leave paid national holidays and paid competitive benefits from financial and education to well-being and beyond at 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 withTargetData Sciencesmeans the chance to help develop and managestate of the art predictivealgorithmsthatuse data at scale to automateand optimize decisions at scale. Every scientist on Targets Data Sciences team can expect to do modeling and data science develop software with highly performant code elevate Targets culture and apply retail domain knowledge.

As a Lead Data Scientist - Recommendations you will provide technical leadership for the machine learning systems that power Targets 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 Targets 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 Targets 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 Targets 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 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 for a Remote or Hybrid (known internally at Target as Flex for Your Day) work arrangement based on Targets needs. A Remote work arrangement means the team member worksfull-time from home oran alternatelocation thats not a Target location does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team members core role may be performed either remote or onsite at a Target location depending upon what your role team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location unless otherwise prescribed by Target.

Benefits Eligibility

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In compliance with state and federal laws Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process please reach out to Non-accommodation-related requests such as application follow-ups or technical issues will not be addressed through this channel.

Application deadline is : 10/29/2026