Lead Data Scientist - Generative AI (applied ML, deep learning, LLMs)

The pay range is $126,600.00 - $227,900.00

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 – GENERATIVE AI

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. You’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Digital/Ecommerce, Marketing, Supply Chain Optimization, Search and Personalization. Every Applied Data Scientist on Target’s team can expect data modeling and software/product development of highly performant code for model performance to elevate Target’s culture and apply retail domain knowledge.

As Lead Data Scientist – Gen AI, you’ll join a Data Sciences team responsible for initializing and helping launch GenAI features, developing centralized GenAI tools/services, and building organizational capabilities around GenAI. Working closely with application teams, you’ll facilitate optimal scaling and adoption of GenAI features, influence technical development roadmap, which includes designing and developing at-scale GenAI system architectures, prompt development & tuning, creating optimal model selection strategy, continuous monitoring & evaluation mechanisms, etc. Based on your understanding of GenAI tools and business requirements, you’ll help develop centralized tools and services to evaluate and control GenAI model output quality across the enterprise. Given this is a rapidly evolving space, you will be required to stay up to date with emerging trends in the industry and leverage your experience as well as expertise in building applied machine learning / deep learning solutions to fine-tune pre-trained GenAI models when needed. We will utilize Agile principles, follow best-practice software design, participate in code reviews, and create a maintainable and well-tested codebase with relevant documentation. At an organizational level, you’ll conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.

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

About you:

• PhD or MS in Quantitative discipline (Science, Tech, Engineering, Mathematics) and 6 plus years of professional experience or equivalent industry experience
• Hands-on experience in developing and deploying real-world GenAI-based applications -including system architecture design, prompt development, appropriate model selection, evaluation, latency/cost optimization techniques, fine-tuning models, etc.
• Demonstrated hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired
• Extensive experience in applied ML and deep learning frameworks
• Strong analytical thinking skills with the ability to creatively solve business problems, innovating new approaches where required
• Exceptional knowledge of mathematical and statistical concepts, algorithms, and c