Professional Overview
Data science and experimentation professional with 5+ years applying Python, SQL, predictive modeling and statistical methods to consumer products. Work includes NLP, topic tagging, article-level named entity recognition, embedding-based relevance, A/B testing, power analysis and causal inference. At DB Corp., collaborated with ML engineers on feed personalization and evaluated ranking candidates through offline simulations and A/B tests, improving feed CTR by 10% across 700K–900K DAUs. Retention experiments lifted WAU by 20%; monetization experiments generated Rs. 3M incremental revenue. At Groww, SQL and Mixpanel analysis guided fixes that lowered order failures by 15% and lifted SIP conversion by 10%. At Magicpin, predictive risk models and operational interventions lowered cancellations from 10% to 4%. Tools include scikit-learn, pandas, NumPy, Snowflake, Airflow, Tableau and Mixpanel.
Experience
Employment Type
Education
Field of Study: Computer Science
Areas of Expertise
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
