Lead Applied Data Scientist - Recommendations (Contextual Bandits, Reinforcement Learning)

Target is hiring a Lead Applied Data Scientist - Recommendations (Contextual Bandits, Reinforcement Learning) for a remote role open to applicants in United States. It pays $132k-$238k a year and Level rates it ; you can apply on Target.

Level's read on this job

Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
This is listed as a remote role.
The posting mentions PyTorch and JAX among its tools and skills.
Level classes it as a lead role.
Target has 1,600+ other open roles on Level.

AI in this role

pytorchjax

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 for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs.  A Remote work arrangement means the team member works full-time from home or an alternate location that's 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 member's 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

Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_E

Americans with Disabilities Act (ADA)

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 candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.  

Application deadline is : 11/05/2026

How we rate this

Lead Applied Data Scientist - Recommendations (Contextual Bandits, Reinforcement Learning) at Target rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Lead Applied Data Scientist - Recommendations (Contextual Bandits, Reinforcement Learning) is an open job at Target.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $132k-$238k a year.
The role is based in 1000 Nicollet Mall, Minneapolis,MN 55403-2542 and is marked remote.
The job was posted on October 6, 2026.
Seniority: lead.
Applications are handled by Target. Apply on Target

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorchJAX

Also common in data scientist jobs at this level

LLM AWS NLP RAG scikit-learn MLOps

Pay

This job starts at: $132k
Typical data scientist job: $170k

This posting starts 22% below the typical data scientist job. See data scientist jobs

Questions you could be asked

What's a project where you used PyTorch hands-on?
Walk me through how you've used JAX in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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