Data Scientist
Indexed description
Website: Visit Website
LinkedIn: Visit LinkedIn
Business Type: Startup
Company Type: Product
Business Model: B2B
Funding Stage: Series D+
Industry: FinTech, payments
Salary Range: ₹ 15-20 Lacs PA
Job Description
The growing volume, complexity, and regulatory scrutiny of financial crime and compliance risks demand advanced, data-driven capabilities that can no longer be effectively supported through traditional analytics or manual processes. The Compliance Data Scientist will play a key role in strengthening Nium’s ability to identify emerging risks, optimise controls, meet regulatory expectations, and improve operational efficiency across the compliance function.
This role addresses a critical capability gap and directly supports strategic priorities such as automation, risk-based decision-making, model optimisation, data quality enhancement, and regulatory assurance. It is also specifically intended to enable the transition of compliance systems toward advanced AI and machine learning solutions, including next-generation 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
- Understand the coverage and accuracy of the existing rules for anti-money laundering and financial crimes
- Support rules management process to ensure rules are performing to expected thresholds
- Support 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
- Leverage advanced analytics to understand cause and effect relationships
- Understand data quality and labelling, perform advanced analysis to identify high predictive strength variables, and work with technology teams on availability of variables.
- 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.
- Degree in Statistics, Mathematics, Data Science, Economics, or related quantitative field
- 2-3 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
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