Data Scientist I

About ALLEN Digital

ALLEN Digital is a leading EdTech platform supporting students preparing for JEE, NEET, and K-12 programs. We leverage data and AI to deliver personalized learning experiences at scale through performance analytics, adaptive content, and intelligent study systems.

About the Role

We are looking for a Data Scientist I to build and deploy high-impact AI/ML solutions across:

• Personalized and adaptive learning journeys
• NLP/LLM-based conversational experiences for learning
• Multi-modal content generation
• Advanced test insights generation
• Content taxonomy and knowledge graph creation

This role involves solving real-world problems end-to-end from problem definition to production deployment with a strong focus on measurable impact.

Key Responsibilities

• Design, build, and deploy ML models to solve business problems
• Work with large-scale student and content datasets to extract insights
• Develop ranking, recommendation, sequencing models for learning journeys and
• content classification, generation and RAG pipelines for chatbot applications
• Collaborate with product, engineering, and academic teams to translate requirements into ML solutions
• Define and track evaluation metrics aligned with user engagement and learning outcomes, and iterate based on results
• Keep track of new developments in AI and propose bold new experiments

Qualifications

• 1–2 years of experience in Data Science / Machine Learning
• Strong programming skills in Python
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Solid understanding of statistics, modeling, and experimentation
• Strong curiosity with emergent AI tech and a tinkering mindset to try new applications

Preferred Skills

• Experience working with large-scale datasets
• Exposure to EdTech, learning systems, or knowledge tracing
• Strong problem-solving and communication skills
• Hands-on experience with prompt engineering, fine-tuning, or RAG pipelines
• Experience with ranking, recommendation systems, or user behavior modeling
• Familiarity with embeddings, collaborative filtering, or sequence-based models