Applied Data Scientist – Fraud Prevention

Requirements

• Prior experience in fraud prevention analytics, preferably within an SME or retail lending environment
• Experience developing and deploying machine learning models in a local and cloud environment
• Strong command of statistical inference and supervised machine learning stack (scikit-learn, pandas, numpy, jupyter). Solid knowledge of Python for data extraction, transformation and analysis
• SQL proficiency for working with data from multiple sources including internal data and external feeds
• Demonstrated success in systems integration and analytics delivery
• Commercial awareness with strong communication skills and the ability to influence stakeholders
• (Desirable) Lending, fintech and regulated sectors work experience
• (Desirable) Working with web applications, cloud data stacks and event driven architecture (we run on ruby on rails, python, aws, github)
• (Desirable) Hands‑on working with c...