Data Scientist

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Rocket Learning

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2020

📚 Education

🌍 Social Impact

🤖 Artificial Intelligence

Education • Social Impact • Artificial Intelligence

Rocket Learning is an India-focused early childhood education organization that transforms public pre-schools (Anganwadi centers) into play-based, joyful learning hubs. Using an AI-powered digital platform and localized bite-sized content, they support parents, train and certify daycare educators, and run community peer groups (including WhatsApp) while providing policy and technical support to government systems. Rocket Learning reports large-scale reach across India (claims in materials: ~6M children and parents, 400K Anganwadi workers, presence in 16 states/UTs and 200+ districts) and emphasizes measurable outcomes (e. g. , ~75% of children school-ready and improvements in learning time and behavior).

📋 Description

• Design, build, and deploy ML and LLM-based systems that drive personalization, assist teachers, and improve programs • Develop, evaluate, and deploy ML, deep learning, and LLM models • Own the end-to-end data science lifecycle from problem definition through deployment and monitoring • Build reproducible, well-documented model workflows and pipelines • Implement model QA/QC, including validation, drift detection, and experiment logs • Collaborate with product and domain teams to shape modeling strategies • Continuously improve performance, documentation, reliability, and processes

🎯 Requirements

• 3–6 years of experience in applied ML, ML engineering, NLP, or LLM development • Strong fundamentals in statistics, ML algorithms, and deep learning • Python proficiency, including pandas, NumPy, scikit-learn, and PyTorch/TensorFlow • Experience with ML workflow tools such as MLflow, experiment tracking, and registries • Experience with LLMs, fine-tuning, embeddings, vector stores, and RAG • Experience deploying models through APIs or containerized workflows • High ownership, clean engineering, and excellent documentation • Excellent communication and collaboration across teams • Curiosity, strong fundamentals, and a bias for shipping reliable systems