Sr Applied Data Scientist - Search and Browse (applied ML, LLMs, ML Ops)

Target

Sunnyvale (CA)

Hybrid

USD 118,000 - 211,000

Full time

20 hours ago
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Benefits offered by this job

401(k)
employee discount
short term disability
long term disability
paid sick leave
paid national holidays
paid vacation

Job summary

Target is seeking a Sr Applied Data Scientist focused on search ranking to power our digital experiences. You will build and deploy scalable ML models, conduct online/offline experiments, and collaborate with product and infra teams to optimize relevance and engagement.

Join our Search & Browse Data Science group to advance semantic retrieval, vector search, and GenAI-enabled discovery at scale. This hybrid role requires strong Python/SQL coding, and a passion for data-driven decision making.

Qualifications

  • PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics or related quantitative discipline.
  • 3+ years of industry experience in Machine Learning, Data Science, Search, NLP, Personalization or related ML systems.
  • Strong experience with retrieval/ranking systems, semantic search, NLP, vector search, or related ML domains.
  • Strong coding skills in Python and SQL; experience in distributed data processing ecosystems.

Responsibilities

  • Develop and deploy scalable ML models for search ranking, browse personalization, semantic retrieval, and query understanding systems.
  • Design offline and online experiments to improve relevance, engagement, conversion, and customer satisfaction.
  • Build scalable feature pipelines, evaluation frameworks, and ML workflows for production systems.
  • Mentor junior scientists and collaborate across teams to improve Search and Browse experiences.

Skills

Python
SQL
Distributed data processing
NLP
Vector search
GenAI/RAG systems

Education

MS or PhD in Computer Science, Statistics, Applied Mathematics, Physics

Job description

Pay range: $118,000.00 - $211,000.00

JOIN TARGET AS A SR APPLIED DATA SCIENTIST – SEARCH RANKING
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 Applied Data Sciences team at Target 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 Search, RecSys, Supply Chain 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, Supply Chain Optimization, Network Security and Personalization rely on. Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Target’s culture and apply retail domain knowledge.

About Our Search And Browse Team

The Search and Browse Applied Data Science team builds the core relevance, retrieval, ranking, and personalization systems that power Target’s Digital experience. We develop scalable ML systems that improve product discovery, semantic search, browse relevance, and customer engagement across Mobile and Web platforms.

E-commerce Search is rapidly evolving with advances in LLMs, semantic retrieval, and conversational AI. We are building next-generation discovery experiences that help millions of guests find the right products quickly and intuitively across massive and constantly changing retail catalogs.

Our team is solving large-scale Search challenges at enterprise scale, including natural language and long-tail search, semantic retrieval, zero-shot item understanding, and AI-native commerce discovery experiences operating at 10K+ QPS with strict latency and reliability requirements.

As a Sr Data Scientist – Search You Will
  • Develop and deploy scalable ML models for search ranking, browse personalization, semantic retrieval, and query understanding systems
  • Design and execute offline and online experiments to improve relevance, engagement, conversion, and customer satisfaction
  • Build scalable feature pipelines, evaluation frameworks, and ML workflows for production systems
  • Apply modern ML techniques including embeddings, retrieval/ranking models, transformers, NLP, vector search, and GenAI/RAG systems
  • Improve query understanding, catalog understanding, semantic retrieval, and long-tail search relevance across large retail catalogs
  • Partner closely with Product, Engineering, and Infrastructure teams to align technical solutions with business priorities and operational requirements
  • Drive data-informed decision making through deep analysis, experimentation, and business impact measurement
  • Balance model quality with latency, scalability, reliability, and infrastructure efficiency in large-scale production systems
  • Contribute to best practices in experimentation, ML engineering, and operational excellence
  • Mentor junior scientists and collaborate across teams to improve Search and Browse experiences

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 Computer Science, Statistics, Applied Mathematics, Physics or related quantitative discipline
  • 3+ years of industry experience in Machine Learning, Data Science, Search, NLP, Personalization or related ML systems
  • Exceptional experience and understanding with retrieval/ranking systems, semantic search, NLP, vector search, or related ML domains
  • Strong demonstrated coding skills in Python and SQL with experience in distributed data processing ecosystems
  • Demonstrated experience building and deploying end to end production ML systems
  • Strong understanding of production ML system tradeoffs including latency, scalability, reliability, and operational excellence
  • Experience with modern ML approaches such as embeddings, transformers, semantic retrieval, RAG systems, or GenAI technologies
  • Experience designing experiments and interpreting online/offline metrics
  • Strong problem-solving skills with the ability to independently drive projects in moderately ambiguous environments
  • Very good communication and cross-functional collaboration skills
  • Constant learner mentality who stays current with new and evolving AI technologies via formal training and self-directed education

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ in Sunnyvale, CA or MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.

Target will consider for employment qualified applicants with criminal histories in a manner consistent with the San Francisco and City of Los Angeles Fair Chance Ordinances.

Benefits Eligibility

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.

  • 401(k)
  • employee discount
  • short term disability
  • long term disability
  • paid sick leave
  • paid national holidays
  • paid vacation

Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.

Americans With Disabilities Act (ADA)

In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.

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