Sr Applied Data Scientist - Item Recommendations (applied ML, PyTorch, ML Ops)

About the role

The pay range is $98,000.00 - $176,000.00. 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.

Responsibilities

• Work on the Target Data Science Recommendations team collaborating with data scientists, machine learning engineers and product managers to build and augment our AI-driven digital Recommendation products.
• Perform data exploration and analysis, implement algorithmic solutions given specifications, push solutions to our production environment, and analyze performance and trade-offs.
• Communicate complex technical concepts and results to both technical and non-technical audiences.
• Translate business problems into scalable data science solutions.

Requirements

• MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or relevant work experience
• 3 plus years of experience developing machine learning models using deep learning frameworks such as PyTorch or JAX
• Experience building recommendation, personalization, search, ranking or retrieval systems at scale
• Strong programming skills in Python and SQL
• Demonstrated experience with optimization, statistics, probability and experimental design
• Experience evaluating models through offline analysis on large-scale datasets and online experimentation, including statistical analysis and interpretation of results
• Extensive experience leveraging generative AI tools to accelerate development, experimentation and model delivery

Qualifications

• Understanding of Agile principles
• Follow best-practice software design
• Participate in code reviews
• Create a maintainable and well-tested codebase with relevant documentation
• Document and present work to technical and non-technical peers
• Leverage knowledge on business priorities and strategic goals to build requirements and solutions for each business need