Job Opportunity Posted today Updated 28 Sep 2026

Data Scientist

Company
Location

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
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