# Data Scientist - Recommendation Systems

**Company:** [Apna](http://jobs.workable.com/companies/oGcPwdAqKGbezdH7GyyVKX.md)
**Location:** Bangalore, India
**Workplace:** on site
**Department:** Engineering

[Apply for this job](http://jobs.workable.com/view/d97babf9-e099-4381-95cb-9b8a5a181049)

## 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