Sr Data Scientist

About the role

Nium builds the global infrastructure that powers real-time cross-border payments for banks, fintechs, and enterprises worldwide. The company was founded with the goal of delivering tomorrow's payments infrastructure today, and it now moves nearly $60 billion in payments each year across 190 countries and 100 currencies. This Senior Data Scientist position focuses on developing AI and machine learning models that identify financial crime and credit risks while keeping those models auditable, explainable, and aligned with data privacy regulations. The role is central to modernizing compliance operations and supporting the transition of compliance systems toward advanced, data-driven artificial intelligence and machine learning solutions, particularly in areas such as Transaction Monitoring detection models.

Key facts

What you'll do

• Design and build AI and machine learning models to detect fraud and credit risks across payment transactions.
• Ensure all developed models are auditable, explainable, and compliant with applicable data privacy laws and regulations.
• Support the transition of existing compliance systems toward advanced, data-driven artificial intelligence and machine learning solutions.
• Develop and refine Transaction Monitoring detection models to identify emerging financial crime risks in real time.
• Optimize model performance through iterative testing, validation, and improvement cycles focused on precision and recall metrics.
• Collaborate with compliance and engineering teams to integrate models into production workflows and operational processes.
• Drive data-quality improvement initiatives to ensure training data is accurate, complete, and fit for model development.
• Implement risk-based decisioning frameworks that enable automated, intelligent flagging of suspicious activities and transactions.
• Create documentation and model cards that make complex model behavior transparent and understandable to stakeholders.
• Work on automation of compliance workflows to reduce manual effort and increase operational efficiency across the team.
• Conduct exploratory data analysis on large-scale transactional datasets to uncover patterns and inform model features.
• Partner with regulatory and audit teams to validate model outputs and ensure alignment with industry standards.

Requirements

• Bachelor's or Master's degree in a quantitative field such as computer science, statistics, mathematics, or engineering.
• Strong experience with machine learning model development, including supervised and unsupervised learning techniques and methodologies.
• Proficiency in Python and familiarity with data manipulation libraries such as pandas and NumPy for analytical work.
• Understanding of data privacy regulations and the ability to design models that respect legal and compliance constraints.
• Experience working with large-scale transactional or financial datasets in a production or near-production environment.
• Solid grasp of model evaluation metrics, validation strategies, and techniques for preventing overfitting and data leakage.
• Familiarity with version control tools such as Git and collaborative software development practices in team settings.
• Ability to communicate complex technical findings clearly to both technical and non-technical audiences across the organization.
• Hands-on experience with SQL for querying, joining, and aggregating data from relational database systems.
• Track record of delivering machine learning models that have been deployed into production and generated measurable impact.

Nice to have

• Experience with Transaction Monitoring systems or financial crime detection platforms in a regulated industry setting.
• Knowledge of explainable AI techniques such as SHAP, LIME, or similar model interpretation frameworks for transparency.
• Exposure to cloud-based machine learning platforms like AWS SageMaker, Google Vertex AI, or Azure ML for model training.
• Background in working within cross-functional teams that include compliance officers, risk analysts, and software engineers.
• Familiarity with regulatory frameworks such as AML, KYC, and sanctions screening in the financial services domain.

Skills & tools

• Python programming for data analysis, statistical modeling, and machine learning model development and deployment.
• SQL for querying, joining, and managing large relational and non-relational databases efficiently.
• Machine learning frameworks such as scikit-learn, XGBoost, or similar gradient boosting libraries for model building.
• Data visualization tools including matplotlib, seaborn, or Plotly for communicating model insights and results clearly.
• Jupyter Notebooks or equivalent interactive development environments for experimentation, prototyping, and iterative model refinement.
• Familiarity with MLOps practices, model monitoring, drift detection, and deployment pipelines in production settings.

Practical notes

• This role is based in Nium's Bangalore office and is expected to be performed on-site or in a hybrid arrangement.
• The position reports into the compliance or data science team and works closely with cross-functional partners across the organization.
• Nium is a high-growth company that raised US$50 million in Series E funding in 2024 at a US$1.4 billion valuation.
• The company operates in over 40 regulated markets and holds regulatory licenses across those jurisdictions.
• Nium is co-headquartered in San Francisco and Singapore with offices in 14 markets worldwide.
• In March 2026, Nium delivered the largest month in its 11-year history with record revenue, record volumes, and EBITDA profitability.
• The company moves nearly $60 billion in payments annually, almost entirely for enterprises, across 190 countries and 100 currencies.
• Nium's payout network spans 190+ countries and 100 currencies, with 100+ corridors in real time, powering transfers to accounts, wallets, and cards.
• The company supports local collections in 35 markets and is a principal card issuer on Visa, Mastercard, Discover, and UATP, issuing over 50 million card tokens every year.
• Nium has been recognized as one of CNBC's World's Top Fintech Companies 2025, winner of Best Cross-Border Payments Solution at the PayTech Awards, and included in FXC Intelligence's Top 100 Cross-Border Payments Companies list.
• The B2B payments market is projected to hit US$175 trillion by 2030, and Nium is positioned to shape the future of global money movement.

About the company

's legal and regulatory obligations in the Americas region, and help drive our expansion into new markets. This role requires strong familiarity with US money transmission licensing (MTLs), cross-border payment systems and regulations, US bank sponsorship, and financial services laws to help us continue to drive innovation and accelerate our licensing and growth plans for the region.