Jacob Paul

About

Data science professional with experience across automation engineering, analytics, and enterprise delivery, including specializing in machine learning, financial risk modeling, and data analytics. Proven track record of developing production-ready machine learning solutions across financial services, including banking, payments, trading risk, and insurance analytics. Expert in Python, SQL, Databricks, and Azure cloud environments with strong experience in big data processing (80M+ records), anomaly detection, and enterprise-scale ML deployment using CI/CD and containerization frameworks. Modeling & Forecasting: Time-Series (GARCH), XGBoost, Random Forest, Gradient Boosting, Demand Forecasting, Risk Scoring, Anomaly Detection, Model Calibration, A/B Testing

Experience

• ML engineer / data scientist
  Scale-up or enterprise · 2021 — present

  Owned model lifecycle: training, deployment, monitoring, and incident response. Shipped GenAI features (RAG, eval harness) with product and data platform on AWS or GCP.

• Data scientist / analyst (prior role)
  Previous employer · 2018 — 2021

  Analytics and early ML: experimentation, dashboards, and first models in production. Replace with your titles, team size, and business KPIs.

AI projects

• Personal AI / data project

  POC or internal tool with Python, PyTorch, MLOps, SQL: ML pipeline, RAG assistant, automation, or analytics. GitHub or demo link when possible.

  Ganloss recruiters often review projects before reaching out.