Head Of Data Science

02 ott - Roma
Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Head Of Data Science & Credit Risk based in Italy.
As Head of Data Science & Credit Risk, you will lead the strategy behind ML-powered underwriting and credit risk decisioning across multiple fast-growing markets.
You will own the full lifecycle of risk models, from development and deployment through monitoring, experimentation, and measurable business impact.
The role combines deep technical leadership with responsibility for credit policies, portfolio performance, and responsible lending practices.
You will build and mentor a high-performing team of data scientists and risk analysts while remaining actively involved in complex technical challenges.
Working closely with Engineering, Product, Finance, and executive stakeholders, you will turn advanced analytics into practical decisions that support sustainable growth.
You will help improve approval rates, automate decisioning, identify new customer segments,



and strengthen portfolio health through data-driven strategies.
This is a greenfield leadership opportunity in a mission-driven fintech environment focused on expanding fairer and more accessible financial services.
Accountabilities ML and model development: Lead the design, testing, deployment, and ongoing improvement of machine learning models for credit decisioning, fraud detection, risk segmentation, customer value, monetization, and marketing attribution.
Underwriting innovation: Develop underwriting algorithms using alternative data sources to strengthen risk assessment while responsibly expanding access to financial services.
Real-time decisioning: Build and scale real-time or near-real-time scoring models across multiple markets and products.
Model governance: Ensure models are interpretable, robust, fair, and reliable, with appropriate monitoring for accuracy, feature stability, performance, and drift.
MLOps: Establish strong

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