Lead Data Scientist- Comp Intel

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 Merchandizing, Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Team Overview Target- Data Science Competitive Intelligence team is offering an exciting opportunity to solve state-of-the-art problems for Competitor Product matching. The team is rapidly growing and creating massive business impact by building cutting edge systems. We use NLP, deep learning, classical machine learning, t ransformers based architectures, and GenAI/Agentic AI (including RAG pipelines, LLM-powered agents, and tool-use frameworks) to build best in-class data products . As we build the future of Competitive Intelligence, we are looking for driven and passionate individuals with deep expertise in developing AI/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, productionization and ongoing upkeep of AIML systems across Competitive Product Classification, Matching and Validation. 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 AIML modeling, experimentation (offline + online), and engineering systems for scalability, latency, and reliability, including t ransformer based models, embedding systems, and retrieval-augmented generation (RAG) pipelines. Developing a multiyear vision for key ML & AI capabilities Competitive Intelligence, 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 anization Preferred Domain Experience We’re looking for strong domain depth and evidence of impact in the following: NLP / Deep Learning / Agentic AI & GenAI / Search & Information retrieval (e-commerce or large-scale Retail or consumer products preferred), including Transformers, semantic search, vector databases, RAG systems, and autonomous/agent-based workflows 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 AIML systems and measurable business impact Deep expertise in modern ML techniques including deep learning, NLP, GenAI, and Agentic AI approaches (such as Transformers, LLMs, RAG, and multi-agent systems), 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 on GCP or similar cloud provider. 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 Product similarity/Classification or similar use-cases, including prompt engineering, context management, and grounding strategies 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 AIML systems at scale: latency/throughput constraints, model monitoring, drift detection, experimentation platforms, and production incident learnings, including LLM system evaluation, retrieval quality metrics, and agent reliability/observabilit y Know More About Us here: Life at Target - Benefits - Culture-