AI & Data
Data Scientist Intern
About the role
As a Data Scientist Intern, you will work on the machine learning and data science that powers RevRag AI's Voice and In-App AI Agents, from analysing conversation, call, and usage data to building, fine-tuning, and evaluating models that improve agent quality in production.
This role is focused on practical, applied data science, not academic research. You'll turn messy, real-world BFSI data into models, experiments, and insights that ship.
Key Responsibilities
- Explore and analyse large conversation, call, and usage datasets to surface patterns, insights, and improvement opportunities.
- Build, train, and evaluate ML models for classification, scoring, and quality tasks across the agent platform.
- Fine-tune and adapt LLMs and smaller models for specific BFSI use cases.
- Design evaluation pipelines and metrics to measure model and agent performance (accuracy, reliability, business impact).
- Read relevant AI and ML research and implement useful ideas from papers.
- Run structured experiments, track results, and document findings clearly.
- Work with engineers to integrate models into production workflows.
- Build data pipelines and tooling for feature engineering, labelling, and analysis.
Technical Skills
- Strong understanding of Machine Learning and Artificial Intelligence fundamentals, including supervised and unsupervised learning, deep learning basics, and common model architectures.
- Good grasp of the mathematical foundations behind machine learning models, including linear algebra, probability, statistics, calculus, and optimization techniques.
- Comfortable reading and understanding AI and ML research papers and implementing ideas from them when required.
- Hands-on experience with model fine-tuning through academic projects, internships, research work, or personal projects.
- Familiarity with Python and popular ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Analytical mindset to evaluate model outputs and data quality.
- Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Nice to Have
- Published or co-authored AI and ML research papers, or active contributions to open-source AI projects.
- Experience participating in AI and ML hackathons, research initiatives, or Kaggle competitions.
- Exposure to LLMs, embeddings, and vector databases.
- Experience with data tools (Pandas, NumPy, SQL) and visualization.
- Exposure to cloud platforms (AWS, GCP).
What You'll Learn
- How to apply data science and ML in real production AI systems.
- Fine-tuning and evaluating models for real BFSI use cases.
- Turning messy real-world data into models and insights.
- Building evaluation pipelines and measuring what actually matters.
- How models behave under real user conditions.
Success in This Role
- Ship measurable improvements to model or agent performance.
- Deliver clean, well-documented experiments and analyses.
- Turn data into decisions that influence the product.
- Demonstrate structured experimentation and strong learning velocity.
About RevRag AI
RevRag AI is a Bengaluru-based deep-tech startup building production-grade Voice AI and LLM-powered automation for customer-facing workflows. Our multilingual, in-app AI agents plug directly into BFSI journeys, improving digital onboarding, sales, and support while cutting operational cost by up to 70%.
We work with leading BFSI organisations including Mahindra Finance, Motilal Oswal, PayTM Insurance, PhonePe, KreditBee, Razorpay, Udaan Capital, Kissht, PolicyBazaar, InsuranceDekho, Open Capital, and EaseBuzz.