Description :

About the Role :

We are looking for a Senior Data Scientist to join our Search Squad and help build scalable search relevance and semantic retrieval systems for a large product catalog. You will work on improving how user queries map to products using modern ranking, retrieval, and machine learning techniques.

This role is ideal for candidates with strong experience in Search, Information Retrieval, Semantic Search, Ranking Models, Recommendation Systems, or NLP-driven retrieval systems.

Key Responsibilities :

- Build and optimize search ranking and retrieval models using Learning-to-Rank (LTR), LambdaMART, neural ranking, and hybrid retrieval approaches.

- Improve query understanding through tokenization, normalization, semantic matching, and embedding-based retrieval.

- Develop semantic search and vector search pipelines using embeddings and dual encoder architectures.

- Work with user behavior and implicit feedback signals including clicks, CTR, dwell time, add-to-cart, and conversions.

- Design and evaluate ranking metrics such as NDCG, MAP, CTR, CVR, and Recall.

- Conduct A/B experiments to improve search relevance and online user experience.

- Collaborate closely with product, engineering, and business teams to balance relevance quality with business goals.

- Analyze search performance and identify opportunities to improve discovery and personalization.

Required Skills :

- Strong experience in Python and SQL

- Experience with Search Ranking / Search Relevance systems

- Knowledge of Learning-to-Rank (LTR), LambdaMART, LambdaRank, or Neural Ranking

- Experience in Semantic Search, Embeddings, Vector Search, or Information Retrieval

- Hands-on experience with Elasticsearch / OpenSearch / Solr or similar technologies

- Strong understanding of Machine Learning algorithms including XGBoost or LightGBM

- Experience with A/B testing and ranking evaluation metrics like NDCG, MAP, CTR, and CVR

- Good understanding of NLP and query understanding techniques

Good to Have :

- Experience in E-commerce or Marketplace search

- Exposure to Recommendation Systems and Personalization

- Knowledge of Deep Learning for retrieval or ranking

- Experience with RAG or LLM-powered search systems

- Familiarity with vector databases and hybrid search architectures

Experience Required : 4 - 8 Years

Location : Bengaluru (Hybrid)

Employment Type : Full Time / Permanent

Preferred Candidate Profile :

- Candidates from E-commerce, Retail Tech, Consumer Internet, Marketplace, or Product-based companies preferred.

- Strong analytical and problem-solving mindset.

- Product thinking with focus on improving search user experience and relevance.

Education : B.Tech / BE / M.Tech / MS in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, or related disciplines.