Risk&AI Manager

Role overview Lead a customer-facing analytics function that helps large banks, payment networks, and merchants get measurable value from a fraud and financial-crime prevention product. This is a people-management role overseeing a distributed team of risk consultants, data scientists, and business analysts across roughly half a dozen concurrent client engagements.

Responsibilities - Manage a cross-functional team running multiple concurrent client projects focused on fraud and financial-crime detection - Oversee delivery of rules, machine-learning models, and risk strategies that align with client goals and platform best practices - Translate ambiguous business objectives into data-driven technical plans, and guide integration of real-time and batch analytics into client environments - Coach the team through performance reviews, career planning, and ongoing professional development - Partner with engineering, product, and delivery organizations on scope, feasibility, and long-term technical direction - Track emerging fraud patterns and analytic techniques, and recommend platform improvements

Requirements - MSc or PhD in computer science, engineering, applied math, physics, statistics, or another quantitative discipline - Strong background in data science, fraud detection, or real-time decision systems - Hands-on experience with machine learning, scripting in Python or R, and big data platforms such as Spark, Hadoop, or cloud-native pipelines - Prior experience leading technical people in client-facing or cross-functional delivery settings - Ability to navigate ambiguity, translate between technical and business stakeholders, and prioritize under pressure - Strong communication and storytelling skills with both client subject-matter experts and internal teams

Nice to have - Direct experience in fraud, anti-money-laundering, or risk strategy within financial services

Benefits and work setup - Remote role with structured onboarding, mentorship, and shadowing opportunities