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Head of Risk & Compliance, Data Science

Job Description

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.

Role Summary:

  • Responsible for leading the development of AI/ML models to identify risks (such as fraud or credit risk) while ensuring these models are auditable, explainable, and compliant with data privacy laws

  • Enhance the coverage and accuracy of the existing rules for anti-money laundering and financial crimes

  • Establish and run rules management process to ensure rules are performing to expected thresholds

  • Manage, mentor, and develop a team of data scientist/analysts supporting compliance domains such as AML, sanctions, fraud, KYC, conduct, and regulatory reporting.

  • Ensures the integrity, accuracy, and usability of data across compliance and financial crime functions.

  • Develops data dashboards to provide visibility of performance of rules and models

  • Bridge advanced analytics with regulatory requirements and risk management

  • Assess data quality and labelling, perform advanced analysis to identify high predictive strength variables, and work with technology teams on availability of variables.

  • Ensures that data-driven insights strengthen regulatory adherence, operational efficiency, and fraud prevention strategies.

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

What we offer at Nium

We Value Performance: Through competitive salaries, performance bonuses, sales commissions, equity for specific roles and recognition programs, we ensure that all our employees are well rewarded and incentivized for their hard work.

We Care for Our Employees: The wellness of Nium’ers is our #1 priority. We offer medical coverage along with 247 employee assistance program, generous vacation programs including our year-end shut down. We also provide a flexible working hybrid working environment (3 days per week in the office).

We Upskill Ourselves: We are curious, and always want to learn more with a focus on upskilling ourselves. We provide role-specific training, internal workshops, and a learning stipend.

We Celebrate Together: We recognize that work is also about creating great relationships with each other. We celebrate together with company-wide social events, team bonding activities, happy hours, team offsites, and much more!

We Thrive with Diversity: Nium is truly a global company, with more than 33 nationalities, based in 18+ countries and more than 10 office locations. As an equal opportunity employer, we are committed to providing a safe and welcoming environment for everyone.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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