This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Spain.

This is an exciting opportunity to join a fast-growing, remote-first environment at the forefront of fraud prevention and financial risk intelligence. In this role, you will leverage advanced analytics, machine learning, and large-scale data to tackle complex fraud challenges with real-world impact. You will work closely with clients and cross-functional teams to design innovative risk solutions, optimize decision-making, and improve product performance. The position combines hands-on technical work with strategic problem-solving and stakeholder collaboration. Ideal for professionals who enjoy turning data into actionable insights, this role offers significant ownership, exposure to cutting-edge technologies, and the opportunity to influence the future of risk management on a integral scale.

Accountabilities:
- Design, build,



and deploy machine learning models to identify and prevent fraud across a variety of fintech and risk-related use cases.
- Drive a data-first culture by promoting analytical thinking and data-driven decision-making across internal teams and client engagements.
- Develop, monitor, and optimize performance metrics to measure the effectiveness of risk strategies and product outcomes.
- Conduct advanced analyses to uncover insights that improve fraud prevention, approval rates, and overall customer experience.
- Partner directly with clients to understand their fraud challenges and provide clear, actionable recommendations based on data insights.
- Build automated dashboards and self-service reporting solutions using business intelligence tools.
- Collaborate closely with engineering teams to productionize models, improve scalability, and enhance data infrastructure.
- Work cross-functionally with product, business, and engineering stakeholders to translate business requirements into

📌 Senior Data Scientist (España)
🏢 Jobgether
📍 España