Lead Data Scientist - 1:1 Personalization and Custom Audience

The pay range is $128,000.00 - $231,000.00

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 – 1:1 PERSONALIZATION

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. Whether you join our Digital, Optimization 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 Marketing, Ad Tech, Supply Chain Optimization, Forecasting, Search and Personalization rely on.  Every Scientist on Target’s Data Sciences team can expect modeling and applied data sciences of highly performant code for model performance to elevate Target’s culture and apply retail domain knowledge.

About the role:

As a Lead Data Scientist on the Audience team with Target Data Sciences, you’ll lead and drive the development of machine learning models that power one-to-one Personalization at scale.  In this role, you will design, build, and deploy advanced models that deliver highly relevant, individualized experiences across Digital channels. You will collaborate with cross-functional partners in Product, engineering, marketing and data analytics to define strategy, lead experimentation and ensure that personalization drives measurable impact for our guests and business.​

In this role as a Lead Data Scientist, you’ll: 

• Model Development: Design, build, and optimize ML models for one-to-one personalization, including recommendation systems, ranking models, customer propensity models, and reinforcement learning approaches
• Leadership and Strategy: Provide technical leadership to a team of data scientists and engineers, setting the vision and roadmap for personalization
• Experimentation and Measurement: Develop testing frameworks (A/B, multi-armed bandits, causal inference) to rigorously measure the impact of personalization initiatives
• Collaboration: Partner closely with product managers, engineers, and business stakeholders to translate business problems into data science solutions
• Scalability and Deployment: Ensure models are production-ready, scalable, and integrated into digital platforms with high reliability and performance
• Innovation: Stay current on advances in ML/AI (deep learning, embeddings, transformers, LLM’s, reinforcement learning) and evaluate their application for personalization use cases

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

About You:

• MS or PhD in quantitative disciplines – Computer Science, Applied Mathematics, Statistics, Physics or related quantitative industry experience
• 5+ years of applied data sciences experience, preferably with 3+ years of experience in large scale 1:1 personalization
• Proficient in one or more programming language – Python, R, Java or Scala
• Demonstrated experience building and deploying ML models in production environments
• Extensive experience in algorithm design, data structures, testing/measurement and ML Ops (GCP - Vertex AI, BigQuery, Spark, Databricks, Snowflake, etc.)
• Strong background in Machine Learning with hands-on experience in Personalization, NLP, and/or Deep Learning frameworks (T