Lead Applied Data Scientist - Digital Item RecSys; applied ML, deep learning)(Remote Or Hybrid

Pay range: $ - $

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

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 ther you join our Applied Data Sciences or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on.

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 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.

• MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or relevant industry experience
• 5 plus years of experience leading the development, evaluation and deployment of machine learning (ML) solutions while partnering with engineering teams to deliver scalable production systems
• Demonstrated experience building and scaling recommendation, personalization, ranking, retrieval, or search machine learning systems
• Strong programming skills in Python and SQL; experience with deep learning frameworks such as PyTorch or JAX
• Experience leveraging modern AI and Generative AI tools to accelerate development, experimentation and model delivery
• Experience working with large-scale data processing and analytics platforms such as Spark or equivalent
• Deep understanding of machine learning, deep learning, optimization,…