Sr Data Scientist

Hire Today; Bengaluru; Presencial; INR 1 800 000 - 3 000 000; Tempo integral

Resumo da oferta

Nium in Bengaluru is seeking a Senior Data Scientist for its Risk & Governance - Fraud & Loss Prevention team. The role focuses on developing and deploying AI and ML solutions for financial crime, fraud detection, compliance risk and transaction monitoring.

You will work on transitioning compliance systems toward data-driven AI, ensuring models are explainable, auditable, and compliant with regulatory and data privacy requirements, while partnering with legal, product and operations to translate

Qualificações

• Degree in Statistics, Mathematics, Data Science, Economics or related quantitative field.
• 3-5 years of experience in data science, advanced analytics or machine learning.
• Strong analytical and problem-solving skills.
• Ability to communicate technical concepts to non-technical stakeholders.
• Ability to work independently and as part of a global team.

Responsabilidades

• Design, deploy and monitor predictive models and AI algorithms to detect anomalies, fraud and potential compliance breaches.
• Analyze large datasets to identify patterns, anomalies and emerging risks.
• Conduct deep-dive analysis of risk events and identify root causes.
• Validate, cleanse and reconcile data for regulatory reporting; support rules management.
• Build scalable reporting platforms and document data protocols and traceability.

Conhecimentos

Data Science

Advanced Analytics

Predictive Modeling

Transaction Monitoring

Anti-Money Laundering

AML

Anomaly Detection

Data Quality

Data Validation

Data Cleansing

Data Analysis

Regulatory Reporting

Data Privacy

Python

SQL

Formação académica

Degree in Statistics, Mathematics, Data Science, Economics or related quantitative field

Descrição da oferta de emprego

Nium is hiring a Senior Data Scientist for its Risk & Governance - Fraud & Loss Prevention team in Bangalore. The role focuses on developing and deploying AI and machine learning solutions for financial crime, fraud detection, compliance risk and transaction monitoring. The position will help transition compliance systems toward advanced data-driven AI and ML solutions while ensuring models are explainable, auditable and compliant with regulatory and data privacy requirements.

Responsibilities

• Design
• deploy and monitor predictive models and AI algorithms to detect anomalies
• fraud and potential compliance breaches. Analyze large datasets to identify patterns
• anomalies and emerging risks. Conduct deep-dive analysis of risk events and identify root causes. Validate
• cleanse and reconcile data for regulatory reporting. Analyze existing anti-money laundering and financial crime rules and support rules management. Develop dashboards to monitor rule and model performance. Identify high-predictive-strength variables and collaborate with technology teams on data availability. Build scalable reporting platforms and document data protocols. Maintain auditability
• traceability and evidence generation. Partner with legal
• product and operations teams to translate technical findings into actionable business insights.

Skills required

• Data Science
• Advanced Analytics
• Predictive Modeling
• Transaction Monitoring
• Anti-Money Laundering
• AML
• Anomaly Detection
• Data Quality
• Data Validation
• Data Cleansing
• Data Analysis
• Regulatory Reporting
• Data Privacy
• Python
• SQL

Minimum Qualifications

• Degree in Statistics, Mathematics, Data Science, Economics or related quantitative field
• 3-5 years of experience in data science, advanced analytics or machine learning
• Strong analytical and problem-solving skills
• Ability to communicate technical concepts to non-technical stakeholders
• Ability to work independently and as part of a global team

Preferred Qualifications

• Prior experience in financial services, fintech, payments or consulting
• Exposure to financial-crime systems such as transaction monitoring, sanctions screening or case-management platforms
• Experience supporting compliance operations, investigations or model governance
• Experience building and deploying ML models in production environments