Data Scientist - Recommendation Systems

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python Elasticsearch SQL Airflow PyTorch KNN TensorFlow

Job Description

Job Title Data Scientist - Recommendation Systems

Location Bangalore

Experience 3-8 years (flexible based on depth in ML systems)

Job Description

We are looking for a Data Scientist (Recommendations) to design, build, and scale personalized recommendation systems that power discovery, ranking, and user engagement across our products.

Requirements

Key Responsibilities

Recommendation & ML Design and develop recommendation systems including:

  • Collaborative Filtering (user-item, item-item) Content-based and hybrid recommenders
  • Ranking and re-ranking models Embedding-based retrieval (ANN, vector search)
  • Train, evaluate, and iterate on models using offline metrics (NDCG, MAP, Recall@K) and online A/B experiments Production ML & Systems Optimize inference for scale (caching, batching, approximate nearest neighbors)
  • Build real-time and batch recommendation pipelines
  • Monitor model performance, data drift, and system health

Data & Experimentation

  • Work with large-scale datasets (clicks, impressions, transactions)
  • Define success metrics for recommendations (CTR, CVR, retention)

Collaboration

  • Work closely with product, data, and backend teams to translate business problems into ML solutions
  • Contribute to ML best practices, documentation, and system design

Required Skills

Core ML

  • Strong understanding of: Recommendation algorithms Ranking and learning-to-rank
  • Embeddings and similarity search
  • Experience with Python and ML libraries (PyTorch / TensorFlow / Scikit-learn)
  • Data & Systems Strong SQL skills; experience with large datasets
  • Familiarity with vector databases / ANN libraries (FAISS, ScaNN, Elasticsearch/OpenSearch KNN, Milvus)

Good to Have

  • Experience with: Search or feed ranking systems
  • Real-time recommendations
  • Knowledge of: MLOps tools (MLflow, Airflow)
  • Experience in e-commerce, ads, content platforms or marketplaces

What You'll Work On

  • Personalized home feeds and search ranking "People also viewed" recommendations
  • Cold-start and long-tail problems
  • Large-scale experimentation and model optimization

Nice Behavioral Traits

  • Strong problem-solving and system-thinking mindset
  • Ability to balance model quality vs production constraints

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