Sr Data Scientist - Search; Applied ML, NLP, Query Understanding)(Remote Or Hybrid

The pay range is $93,800.00 - $

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. Target cares about and invests in you as a team member so that you can take care of yourself and your family. Eligible team members and their dependents receive 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.

As a Fortune 50 company with more than 350,000 team members worldwide, Target is an iconic brand and one of America’s leading retailers. Working at Target means helping all families discover the joy of everyday life, and we bring that vision to life through our values and culture.

We prioritize relationships, develop talent by creating growth opportunities, and succeed as one Target team. At our core, our purpose is ingrained in who we are, what we value, and how we work. Every time a guest enters a Target store or browses , they experience the impact of Target’s investments in technology and innovation. We’re the technologists behind one of the most loved retail brands, delivering joy to millions of our guests, team members, and communities.

Join our global in‑house Tech team of more than 5,000 software engineers, applied data scientists, architects and product managers striving to make Target the most convenient, safe and joyful place to shop. We use agile practices and leverage open‑source software to adapt and build best‑in‑class technology for our team members and guests, with a focus on diversity and inclusion, experimentation and continuous learning.

The Search and Browse Data Science team builds the core relevance engine and Data Science products that power Target’s digital experience. As a Sr Data Scientist on this team, you’ll work with business partners to provide solutions for business problems in a fast‑paced and global environment. You’ll have the opportunity to design high‑quality, flexible and performant Data Science systems and services ’ll also architect Data Science solutions that capture, process and mine huge datasets in the retail industry.

You will promote innovative thinking and utilize cutting‑edge machine learning algorithms and NLP techniques to improve our mobile and web search systems at Target.

As a Sr Data Scientist, you will influence by interacting within the Data Sciences team and with product teams, performing within the scale and scope of your role by implementing solutions, and contributing to Data Sciences’ and Target’s culture by modeling the culture. You will apply foundational knowledge of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory to perform data exploration and analysis (look at distributions, find anomalies, create simple visualizations, etc.)

and implement algorithmic solutions given specifications while adhering to best practices in model development. We expect you to follow foundational programming principles (best practices, unit tests, code organization, basics of CI/CD, etc.) and maintain a well‑maintainable & tested codebase with relevant documentation. You will develop in one or more approved programming languages (Java, Scala, Python, R), and learn and adhere to best practices in data analysis and data understanding.

Core responsibilities of this job are described in the preceding paragraph. Job duties may change at any time due to business needs.

• 4‑year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
• PhD or MS in Computer Science, Applied Mathematics, Physics or a related quantitative field
• Research and/or industry experience in relevant fields such as information retrieval, machine learning, NLP, recommendation or recommender systems
• Demonstrated…