Data Scientist — MLOps · Causal Inference · Forecasting.
Building ML systems that ship.
About
I'm a BSc Computer Science graduate who spent a year in enterprise IT at TCS, working on production systems and automated workflows before deciding to pursue what genuinely excites me — making machines learn from data.
Today I'm self-transitioning into data science with a focus on causal ML and production-grade ML systems. I hold the Microsoft Certified Azure Data Scientist Associate (DP-100) credential and am actively building a portfolio that goes beyond notebooks into real engineering artefacts.
My core interests sit at the intersection of causal inference, uplift modeling, and MLOps — areas where rigorous statistics meets systems that actually ship to production.
Skills
Projects
Causal ML system implementing T-Learner & X-Learner meta-learners for marketing targeting optimization. Quantifies the incremental revenue impact of campaigns on individual customers, enabling budget allocation to those most likely to respond positively to treatment.
End-to-end ML lifecycle management system for customer churn prediction. Integrates PSI and KS-based data drift detection, a FastAPI prediction endpoint, and automated alerting — demonstrating a production-ready approach to model deployment and monitoring.
Demand forecasting pipeline using National Transmission System (NTS) data alongside weather covariates — specifically Heating Degree Days (HDD) — combined with ensemble models to capture seasonal and temperature-driven consumption patterns in UK gas demand.
Production-grade statistical testing framework with Bayesian, frequentist, and causal inference capabilities across the full experimental lifecycle.
Certifications
Contact
Open to data science roles, freelance projects, and collaborations involving causal ML, MLOps, or forecasting.
adityacharya1104@gmail.com