Senior Data Scientist — Fintech

Outsourceit; Zürich; On-site; CHF 90,000 - 120,000; Full time

Job summary

Outsourceit in Zürich is looking for a Senior Data Scientist to develop credit risk models and fraud detection systems for a mid-size European investment fund. Your role will involve working with proprietary and alternative datasets, requiring deep statistical expertise to deploy models into production.

The ideal candidate should have experience in model validation and monitoring in a regulated finance environment. This is a fixed-term position with strong potential for extension, requiring a work load of 35-40 hours weekly.

Qualifications

• Deep statistical expertise with experience in model deployment.
• Knowledge of production ML models and validation frameworks.
• Experience within regulated finance is beneficial.

Responsibilities

• Build and own credit risk models and fraud detection systems.
• Work with proprietary transaction datasets and alternative data sources.
• Monitor and maintain production ML models.

Skills

Expert‑level knowledge of regression, classification, time‑series, and Bayesian methods.

Fluency in Python (pandas, scikit‑learn, statsmodels).

Complex SQL query optimisation.

Experience in credit risk, fraud detection, or portfolio analytics.

Job description

Arclight Capital Analytics is seeking a Senior Data Scientist to build and own credit risk models, fraud detection systems, and portfolio analytics pipelines for a mid-size European investment fund.

You will work with proprietary transaction datasets and alternative data sources. The role requires both deep statistical expertise and the ability to deploy models into production with rigorous validation frameworks.

Qualifications

• Expert‑level knowledge of regression, classification, time‑series, and Bayesian methods.
• Fluency in Python (pandas, scikit‑learn, statsmodels) and complex SQL query optimisation.
• Experience in credit risk, fraud detection, or portfolio analytics within regulated finance.
• Ability to deploy, monitor, and maintain production ML models with proper versioning.

Fixed‑term with strong likelihood of extension.

Work Load: 35‑40 HRS/WK

CET timezone overlap required for 4 hours daily.