Principal Data Scientist

Experience and Skills

• 8+ years of experience in risk management, underwriting, or credit analytics within fintech, lending, or specialty finance environments
• C1 English level or higher
• Proven track record building AI/ML-driven credit models, risk scorecards, and pricing frameworks
• Strong proficiency with Python, R, SQL, and Excel
• Deep expertise in risk-adjusted pricing, portfolio management, loss forecasting, and modeling techniques (regression, ML, ensemble methods, decision trees, neural networks)
• Experience managing and mentoring small, high-impact data or risk teams
• Solid understanding of cash-flow and alternative-data underwriting

Skills

• Python
• R
• SQL
• Machine Learning
• Credit Scoring
• Risk Management
• Predictive Modeling
• Underwriting
• Portfolio Management
• Loss Forecasting

Projects

This role demands a Principal Data Scientist to lead and scale the risk and underwriting capabilities of a fast-growing fintech platform focused on providing working capital solutions. This is a senior, highly hands-on position where risk, data, and machine learning are treated as core systems rather than support functions. You will own the design, implementation, and continuous optimization of AI-driven underwriting models, risk scorecards, and portfolio strategies. In this role, you will define the long-term vision for risk management at scale while remaining directly involved in model development, feature engineering, and deployment. You will lead and mentor a small, high-impact team of data scientists, setting high technical standards and raising the overall quality bar across the organization. By leveraging alternative data sources and collaborating across product and engineering teams, you will drive fully automated decisioning workflows that directly impact business growth.

Key Responsibilities

• Design, build, and maintain risk scorecards, credit underwriting models, and offer calculation engines using advanced AI/ML techniques
• Establish and lead the end-to-end risk management framework, including credit, operational, and portfolio risk strategies
• Develop and optimize risk-adjusted return strategies, loss forecasting, pricing optimization, and portfolio performance analysis
• Leverage alternative data sources, such as bank, cash flow, behavioral, and third-party data, to improve underwriting accuracy
• Partner with Product, Data, Engineering, and Finance teams to integrate ML models into fully automated decisioning workflows
• Build early-warning systems and real-time monitoring tools using machine learning to detect anomalies, fraud, and emerging risk patterns
• Lead, mentor, and review the work of a small team of data scientists while remaining directly involved in technical execution
• Deliver clear, data-driven reporting to internal stakeholders, board members, and capital partners while ensuring regulatory compliance

Benefits

We provide the opportunity to participate in impactful and technically rigorous industrial data projects that drive innovation and professional growth. Our work environment emphasizes technical excellence, collaboration, and continuous innovation.

Niuro supports a 100% remote work model, allowing flexibility in work location globally. We invest in career development through ongoing training programs and leadership opportunities, ensuring continuous growth and success.

Upon successful completion of the initial contract, there is potential for long-term collaboration and stable, full-time employment, reflecting our long-term commitment to our team members.

Joining Niuro means becoming part of a global community dedicated to technological excellence and benefiting from a strong administrative support infrastructure that enables you to focus on impactful work without distraction.

Nice to Have

• MLOps
• Model Deployment
• Alternative Data
• Automated Decisioning