Data scientist

16 ott - Campobasso
FINVISION

Models and data for credit risk and business decision support
Contract: Full-time, 24-month fixed-term contract within a funded R&D; project.
Location: Remote, with periodic in-person meetings in Campobasso, Brescia or Cassino and at pilot companies.
Salary information will be shared during the first stages of the recruiting process.
Start From November 2026

ABOUT US
110 Laude is an Italian fintech company and spin-off of the University of Molise (UNIMOL). We build FINVISION, a B2B SaaS platform for financial analysis and credit assessment used by banks, SMEs and advisors across Italy. We are hiring for OVERSIK, a 24-month R&D; project with a university as scientific partner: a decision-support ecosystem for business risk assessment, built on what banks and companies actually need and validated with ten pilot companies.

THE ROLE
You will work on the models and data side of the OVERSIK system: scoring, scenarios and the quality of the data collected in the field. You will work alongside the AI Engineer (OVK-01) as a mirror profile: you share the work,



act as each other’s backup and can step in on each other’s areas.

WHAT YOU WILL DO
• Develop and validate models for credit risk assessment, scoring and financial scenarios
• Work on company financial statements and business registry data, building indicators from balance-sheet and cash-flow data
• Define and monitor the quality of the data collected by our field team
• Build and test AI/LLM-based tools for automated financial analysis and reporting
• Bring models into the prototype together with the AI Engineer, and support validation with pilot companies

WHAT WE ARE LOOKING FOR
• Master’s degree (or final-year student) in Data Science, Statistics, Mathematics, Economics, Engineering, computer Science or related fields; PhD students and recent PhDs are welcome
• Solid skills in Python (pandas, scikit-learn) and SQL, and a good grounding in statistics and machine learning
• Level: 1–4 years of practical experience, in

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