Head of Risk & Compliance, Data Science

Nium is the global infrastructure company powering real-time cross-border payments. Founded to deliver the payments infrastructure of tomorrow, today, we are building a programmable, borderless, and compliant money-movement layer that powers transactions between people, businesses, and intelligent systems — enabling banks, fintechs, payroll providers, travel platforms, marketplaces, and other global enterprises to move money instantly, anywhere in the world.

Co-headquartered in San Francisco and Singapore, with offices in 14 markets and team members across 20+ countries, we take pride in a culture anchored in Keeping It Simple, Making It Better, and Winning Together. 2025 was the strongest year in our 10-year history, with record revenue, record transaction volumes, and EBITDA profitability — and we are now entering one of the most dynamic chapters in our journey. We believe the best work happens face-to-face, and we operate a hybrid model with three in-office days per week to strengthen collaboration, alignment, and innovation.

We move over $50B annually across a network that spans 190+ countries, 100 currencies, and 100 real-time corridors. We power fast payouts to accounts, wallets, and cards; enable local collections in 35 markets; and support card issuance in 34 countries — all backed by licenses across 40+ markets.

With over $300M raised to date, Nium offers ambitious builders the opportunity to shape the future of global money movement — at scale.

Key Responsibilities

Define the vision for Data Science in risk and compliance, ensuring alignment with business goals, risk appetite, and regulatory requirements Lead the end-to-end development of ML models (e.g., AML detection, KYC/KYB, fraud scoring, model validation) while ensuring compliance with auditability and fairness standards Knowledgeable about AI and comfortable leveraging AI in different aspects of model development Supports rules and models testing and validation, in coordination with the Product Team. Identifies opportunities to enhance compliance analytics capabilities and automation. Develop, measure, and monitor data risk frameworks, including data quality, integrity, and security

Requirements

Master's degree or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field 12+ years in data science / modeling roles preferably in compliance or financial crime domain. Strong understanding of ETL (Extract, Transform, Load) processes, data modelling concepts and data warehousing Understanding of AML, KYC, sanctions, and regulatory reporting requirements would be preferred Proficient in AI/ML algorithms, statistical modeling, data mining, and languages like Python, R, and SQL Experience in building data / management information dashboards in different environments (Power BI, Qlikview, Qilksense) Familiarity with financialcrime systems and data structures (AML transaction monitoring, sanctions screening engines and fraud detection systems) is a plus. Ability to translate complex datasets into high accuracy good / bad separation decisions Strong written and verbal skills for reporting and stakeholder engagement. Build and manage high-performing teams, fostering a culture of innovation, data science excellence, and compliance awareness