I will build a churn prediction model for finance or insurance

In finance and insurance, a bad prediction doesn't just cost revenue it costs customers, capital, and reputation.

I'm a Senior Analytics Engineer with 8+ years of experience, including 2+ years as a Data Analyst at L'Olivier Assurance (Admiral Group) one of Europe's leading insurance groups. I've built predictive models professionally across risk, churn, and customer value in regulated, data-sensitive environments.

What I build

Churn & retention prediction who's about to leave?

Risk scoring & portfolio segmentation

Lead scoring & conversion probability

Customer LTV & value driver modelling

Fraud detection & anomaly flags

Demand & claims forecasting

Tools

Python · scikit-learn · XGBoost · PyMC · statsmodels · SQL · pandas

What you get

Clean Python notebook · Model validation report · Plain-English business interpretation · Actionable next steps

Who this is for

Insurance companies · Fintech startups · Banks & credit firms · Investment platforms · Risk & actuarial teams

How it works

Share your data and your business problem. I'll recommend the right model and scope before we start.

Insurance-trained · Risk-experienced · 8+ years · Models built for regulated industries.