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Senior Data Scientist, Risk
Not specifiedFull-timeData ScienceFinancial Services
Join a risk-focused data science team developing machine learning, generative AI, and AI-agent solutions for fraud prevention and secure B2B payments.
Responsibilities
- Design, build, and deploy machine learning and generative AI models for risk and fraud detection.
- Lead development of models that identify, classify, and prevent financial risks.
- Define, build, and evaluate AI-agent workflows that triage and explain risk decisions.
- Create reliable evaluation harnesses to support release gating and production accuracy.
- Own data science projects from initial idea through scalable production deployment.
- Contribute to risk data science strategy and identify technical and business opportunities.
- Set high technical standards and drive innovation in AI agents and risk prevention.
Requirements
- At least 7 years of data science experience, or 3 years with a Ph.D.
- Bachelor's degree in computer science, software engineering, mathematics, electrical engineering, statistics, or a related quantitative field.
- Advanced statistical and machine learning experience applied to real-world problems.
- Experience leading complex machine learning projects from initial concept through production deployment.
- Understanding of imbalanced and adversarial data, delayed or noisy labels, and precision-recall trade-offs in risk modeling.
- Experience developing and evaluating generative AI systems and AI agents using foundation language models.
- Experience with large-scale data processing pipelines, cloud computing, and machine learning operations.
- Regular use of LLMs or agentic tools and a demonstrated ability to turn recurring problems into reusable automation.
Nice to have
- Experience in fraud detection, anomaly detection, anti-money laundering, risk modeling, or fintech.
- M.Sc. or Ph.D. in computer science, software engineering, mathematics, electrical engineering, statistics, or a related quantitative field.