
Staff Data Scientist
5 days ago
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.
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