Professional Overview
I’m a Senior Staff Data Scientist with 10 years building GenAI/RAG pipelines, LLM systems, and production ML platforms across retail, IoT, and enterprise domains. I’ve driven $55M+ revenue and 30% CSAT gains through propensity modeling, CLV/retention systems, and scalable MLOps on AWS, Databricks, and Azure. Open to remote roles or relocation.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led ML/GenAI framework design for real-time decision intelligence at scale.
- Built RAG-based LLM pipeline for sentiment analysis, boosting CSAT by 30%
- Built propensity models driving 1M+ customer acquisitions, $55M revenue
- Delivered CLV/retention models via Cox survival and CatBoost, +20% CLV
- Deployed MLOps pipelines on Databricks, MLflow, AWS across teams
Key Achievements / KPIs
- Boosted issue detection 85% and CSAT 30% via GenAI RAG pipelin
- Drove $55M revenue, 1M+ new customers via propensity modeling
- Improved retention 15% and CLV 20% through survival modeling
- Achieved 70%+ accuracy, 65%+ recall on CatBoost classifiers
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led ML/GenAI framework design for real-time decision intelligence at scale.
- Built RAG-based LLM pipeline for sentiment analysis, boosting CSAT by 30%
- Built propensity models driving 1M+ customer acquisitions, $55M revenue
- Delivered CLV/retention models via Cox survival and CatBoost, +20% CLV
- Deployed MLOps pipelines on Databricks, MLflow, AWS across teams
Key Achievements / KPIs
- Boosted issue detection 85% and CSAT 30% via GenAI RAG pipelin
- Drove $55M revenue, 1M+ new customers via propensity modeling
- Improved retention 15% and CLV 20% through survival modeling
- Achieved 70%+ accuracy, 65%+ recall on CatBoost classifiers
Education
Field of Study: Information Technology
Field of Study: Information Technology
Areas of Expertise
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
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.