Staff Data Scientist - ML & Recommendations

Job Description – Staff / Sr. Staff Data Scientist (ML & Recommendations)

Location: Noida / Bangalore

About the Company

PhysicsWallah (PW) is India’s leading edtech platform, founded in 2016 by Alakh Pandey with a mission to make high-quality education affordable and accessible for every student.

What began as a YouTube channel has now grown into a multi-billion-dollar unicorn serving millions of learners through online courses, offline hybrid centres, and test-prep programs for JEE, NEET, UPSC, state boards, and beyond.

With 15M+ app downloads, 2M+ daily learners, and 120+ offline centres across India, PW has transformed the education landscape by combining technology, pedagogy, and affordability. Recognised as a Great Place to Work, the company continues to expand globally, partner with state governments, and pioneer AI-driven innovation in education.

Qualification & Eligibility

• Bachelor’s or higher degree in a quantitative discipline (Computer Science, Statistics, Engineering, Applied Mathematics).

Work Experience

• Minimum 6+ years of experience.
• Startup experience preferred; Edtech work experience is a 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: Collaborate 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 Required

• 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 personalization.