Data Scientist
Job Description
Key Responsibilities :
1. Recommendation Systems
- Design and optimize personalized recommendation engines (collaborative filtering, content-based, hybrid models)
- Build real-time and batch recommendation pipelines for playlists, songs, and content discovery
- Improve CTR, session time, and content consumption through personalization
2. Search & Ranking
- Develop and enhance search relevance and ranking algorithms
- Work on query understanding, typo correction, intent detection, and semantic search etc
- Optimize search-to-play conversion and reduce zero-result scenarios
3. Predictive Modelling
- Build models for Churn prediction, User lifetime value (LTV), Conversion propensity, Cohort Management
- Drive proactive interventions using predictions
4. Experimentation & Optimization
- Design and run A/B tests and multivariate experiments
- Measure impact using key metrics
- Translate data insights into product and growth strategies
5. Data & ML Infrastructure
- Work with large-scale datasets to build scalable ML pipelines
- Collaborate with engineering teams to productionize models
- Monitor model performance and continuously iterate
Required Qualifications
- 7+ years of work experience with Master's degree in Computer Science, Mathematics or a related field
- Hands-on experience with Recommendation systems, Search ranking (Elasticsearch, vector search, embeddings)
- Predictive modeling techniques
- Solid understanding of Machine Learning algorithms, Statistics & probability, Feature engineering & model evaluation
- Strong proficiency in Python & SQL
- Experience with data visualization tools
- Experience with SQL and large-scale data systems (BigQuery, Spark, etc.)
- Familiarity with real-time data processing
- Exposure to MLOps and deployment pipelines
Key Competencies
- Strong problem-solving and analytical thinking
- Ability to communicate complex findings to non-technical stakeholders
- High attention to detail and data accuracy
- Collaborative mindset and ability to work in cross-functional teams
More Info
Key Skills
Vector search
Predictive modeling techniques
Recommendation systems
Feature engineering
Embeddings
Real-time data processing
Search ranking
Data visualization tools
Deployment pipelines
Model evaluation
About Company
Skills:
snowflake , Cassandra, PostgreSQL, Nosql, Docker, Terraform, MySQL, Elasticsearch, Oracle, Python, AWS, SQL Server, HBase, Redis, Sql, Hive, Gcp, Amazon Redshift, Spark, MongoDB, Azure, Airflow, MLflow, Beam, GitHub Actions, Teradata, Luigy, Nifi
Skills:
production deployment , Personalization, Nlp, Gcp, Azure, Python, AWS, feature stores, Generative AI, LLMs, model training, behavioural and event-streaming datasets, search systems, vector databases, a/b testing, embedding-based retrieval systems, video understanding models, MLOps tooling, feature engineering, ML experimentation frameworks
Skills:
Machine Learning, Pyspark, Sql, Nlp, Pytorch, Databricks, Python, Generative AI, LLMs, MLflow, LLM APIs, RAG, Azure AI services
Skills:
Python, R Programming, Sql
Skills:
Pyspark, Tensorflow, Deep Learning, Nlp, Pytorch, Gcp, Machine Learning, Recommender Systems, Azure, Python, AWS, GenAI dev tools and frameworks, Langchain, scikit-learn, AI Agents, HuggingFace, Search engine query pipelines, LangGraph, Langfuse