Lead Data Scientist

About Us

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

Overview about TII

At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

Pyramid Overview

A role with Target Data Science & Engineering 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 Statistics, 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.

Team Overview

Target Search is offering an exciting opportunity to solve state-of-the-art problems in e-commerce search. Target’s Search Technology team is rapidly growing and creating massive business impact by building cutting-edge search systems. We use NLP, deep learning, classical machine learning and LLMs to build best-in-class systems. As we build the future of e-commerce search, we are looking for driven and passionate individuals with deep expertise in developing ML systems at scale and leading high-impact charters. If you are that person, you can expect to be involved in:

• Leading the design, development, and productionization of ML systems across query understanding, content understanding, retrieval, ranking/relevance, and ads/recommendations

• Owning technical direction for a problem area: defining strategy, influencing roadmaps, setting quality bars, and driving execution through a team of scientists and engineers

• Architecting end-to-end solutions that integrate modeling, experimentation (offline + online), and engineering systems for scalability, latency, and reliability
Developing a multi-year vision for key search/relevance capabilities on Target.com, aligned to business outcomes and measurable metrics

• Serving as a technical leader and mentor, raising the bar for scientific rigor, design reviews, and best practices across the org

Preferred Domain Experience
We’re looking for strong domain depth and evidence of impact in one or more of the following:

• Search / Retrieval / Ranking / Relevance (e-commerce or large-scale consumer products preferred)

• Recommendations (personalization, candidate generation, ranking, multi-objective optimization)

• Ads / Sponsored Search (auction systems, relevance, pacing/bidding, ads ranking, CTR/CVR modelling)

About You

• 4-year degree in a quantitative discipline (Science, Technology, Engineering, Mathematics) or equivalent practical experience

• 7+ years of professional data science / applied ML experience (or equivalent), with a strong track record of delivering production ML systems and measurable business impact

• Deep expertise in modern ML techniques including deep learning, NLP, representation learning, and LLM-based approaches, with strong judgment on when to use simpler methods

• Demonstrated ability to lead large, ambiguous problem spaces: framing, solutioning, driving alignment, and delivering through cross-functional partners

• Strong hands-on programming skills in Python, SQL, and Spark, plus comfort working closely with engineering stacks for online inference, data pipelines, and model lifecycle tooling

• Experience with LLM adaptation (e.g., fine-tuning, instruction tuning, preference optimization) and/or agentic workflows (tool use, RAG, evaluation harnesses, orchestration, safety/quality guardrails) applied to Search/Rec/Ads use-cases

• Strong analytical thinking and applied research skills: ability to build evaluation frameworks, perform error analysis, and iterate based on data and user outcomes

• Excellent communication skills: able to influence technical and non-technical stakeholders, write clear RFCs/design docs, and drive decisions in reviews

• Self-driven, results-oriented, and able to operate as a multiplier across teams

Nice to Have

• Publications or accepted papers/posters in industry tracks at top-tier conferences (e.g., SIGIR, KDD, WWW, NeurIPS, ICML, ACL, EMNLP, RecSys), or equivalent demonstrated external technical contributions (open-source, patents, invited talks)

• Experience operating ML systems at scale: latency/throughput constraints, model monitoring, drift detection, experimentation platforms, and production incident learnings

• Experience in multi-objective optimization (e.g., relevance + revenue + fairness + constraints) and online experimentation at high traffic

Know More About Us:

• Life at Target- https://india.target.com/

• Benefits- https://india.target.com/life-at-target/workplace/benefits

• Culture- https://india.target.com/life-at-target/belonging