Sr Data Scientist

Nium provides global infrastructure for real-time cross-border payments. We were founded on the mission to deliver the global payments infrastructure of tomorrow, today. Our platform enables banks, fintechs, and global businesses to move money instantly, everywhere. Co-headquartered in San Francisco and Singapore with offices in 14 markets worldwide, we are entering one of the most exciting chapters in our journey. In March 2026, we delivered the largest month in our 11-year history with record revenue, record volumes, and EBITDA profitability. Today, Nium moves nearly $60B in payments annually, almost entirely for enterprises, while continuing to strengthen an already healthy balance sheet. It is an incredible time to join us, and we are only just getting started. Our payout network spans 190+ countries and 100 currencies, with 100 + corridors in real time. We power seamless transfers to accounts, wallets, and cards, support local collections in 35 markets, and as a principal card issuer on Visa, Mastercard, Discover, and UATP, Nium issues over 50 million card tokens every year. Backed by regulatory licenses in 40+ markets, we make it simple for our partners to onboard, integrate, and scale globally. This scale and innovation have earned us recognition as one of CNBC’s World’s Top Fintech Companies 2025, winner of Best Cross-Border Payments Solution at the PayTech Awards, and inclusion in FXC Intelligence’s Top 100 Cross-Border Payments Companies list. In 2024, we raised US$50 million in Series E funding at a US$1.4 billion valuation to accelerate network expansion, product innovation, and talent growth. With the B2B payments market projected to hit US$175 trillion by 2030, Nium offers ambitious builders the chance to shape the future of global money movement with the scale of a leader and the energy of a high-growth company. The increasing volume, complexity, and regulatory scrutiny of financial‑crime and compliance risks requires advanced, data‑driven capabilities that traditional analytics and manual processes can no longer support. The Compliance Data Scientist will significantly enhance Nium’s ability to detect emerging risks, optimise controls, meet regulatory expectations, and drive operational efficiency across the compliance function. This role fills a critical capability gap and directly supports strategic priorities including automation, risk‑based decisioning, model optimisation, data‑quality improvement, and regulatory assurance. Additionally, this role is specifically designed to support activities related to transitioning compliance systems to advanced, data-driven Artificial Intelligence / Machine Learning solutions e.g. Transaction Monitoring detection models. Role Summary: Responsible for 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 Key Responsibilities: Design, deploy, and monitor predictive models and AI algorithms to detect anomalies, fraud, or potential breaches Conduct deep-dive analyses into risk events, identifying root causes to improve risk strategies and operational workflows Analyze large datasets to identify patterns, anomalies, and emerging risks. Performs data validation, cleansing, and reconciliation for regulatory reporting. Ensure alignment with regulatory requirements by building scalable reporting platforms and documenting data protocols Partner with legal, product, and operations teams to translate complex technical findings into actionable business insights for senior management Maintains auditability, traceability, and evidence generation within systems. Requirements: Degree in Statistics, Mathematics, Data Science, Economics, or related quantitative field 3-5 years in data science, advanced analytics, or machine ‑ learning roles. Proficiency in various model development techniques Prior experience in financial services, fintech, payments, or consulting would be strongly preferred Exposure to financial ‑ crime systems (e.g., transaction monitoring, sanctions screening, case ‑ management platforms). Experience supporting compliance operations, investigations, or model governance. Experience building and deploying ML models in production environments. Strong analytical rigor, proactive problem-solving, and capability to communicate technical concepts to non-technical partners Self-motivated, adept in working individually and as part of a global team