Staff/ Data Scientist

5 days ago

Bengaluru Delhi NCR Noida, India Physicswallah Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Staff/Sr.Staff Data Scientist - ML & Recommendations

Qualification & Eligibility:

  • Bachelor's or higher degree in a quantitative discipline (computer science, statistics, engineering, applied mathematics)

Working Experience:

  • Minimum 6+ years of experience
  • Startup experience preferred, Edtech work experience bonus

Roles & responsibilities:

  • Model Development: Design, train, and deploy recommendation algorithms (collaborative filtering, deep learning, bandits, reinforcement learning, embeddings, etc.).
  • Experimentation: Set up A/B testing frameworks, design evaluation metrics (CTR, engagement, retention, revenue lift), and analyze causal impact.
  • Data & Feature Engineering: Build and optimize pipelines to generate high-quality features from large-scale user, content, and interaction data.
  • Scalability & Systems: Work closely with engineering to ensure models are production-ready, scalable, and low-latency.
  • Domain Leadership: Drive innovation in personalization strategies (multi-objective optimization, cold-start solutions, contextual recommendations, etc.).
  • Mentorship: Provide technical leadership, code reviews, and best practices to other scientists.

Skill Sets:

  • Core ML: Strong background in machine learning fundamentals: supervised/unsupervised learning, regression/classification, probability & statistics.
  • Recommendation Systems: Deep understanding of collaborative filtering, matrix factorization, sequence models, embeddings, two-tower retrieval models, deep retrieval/ranking architectures, and multi-task learning.
  • Programming: Proficiency in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow, JAX). Strong SQL skills.
  • Experimentation: Expertise in A/B testing design, statistical significance, confidence intervals, and bias correction.
  • Systems/Infra Awareness: Familiarity with model serving, feature stores, online/offline training pipelines, and latency optimization.
  • Communication: Ability to translate technical insights into business impact, and influence product/engineering roadmaps.

Good to have:

Experience with big data tools (Spark, Trino, Presto, Hadoop, BigQuery, Redshift).

Leveraging LLMs for personalisation

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