Data Scientist Associate - Fraud Risk

Location: Mumbai, Maharashtra, India

Job Family: Predictive Science

About the Role

At JP Morgan Chase, we are at the forefront of transforming financial services through innovative technology, and our Fraud Data Science team is pivotal in safeguarding our clients and assets. As a Data Scientist Associate in Fraud Risk, based in our dynamic Mumbai office, you will join a high-impact team dedicated to pioneering AI/ML, graph analytics, and LLM-driven solutions to combat evolving fraud threats. This role within the Predictive Science category offers the opportunity to work on cutting-edge projects that directly influence global banking security, leveraging vast datasets from transactions, customer behaviors, and network interactions to build resilient fraud prevention systems. Your primary focus will be developing sophisticated predictive models that detect anomalies in real-time, utilizing advanced techniques like graph neural networks to uncover hidden fraud rings and LLMs to analyze unstructured data for risk signals. You will collaborate with cross-functional teams including risk managers, engineers, and compliance experts to iterate on models, ensuring they meet stringent regulatory standards such as those from RBI and international bodies. In this role, you will contribute to JP Morgan Chase's commitment to ethical AI, emphasizing explainable models that enhance trust in our financial ecosystem while driving operational efficiency. This position is ideal for a passionate data scientist eager to make a tangible impact in the financial services industry. You will thrive in a supportive environment that fosters innovation, with access to state-of-the-art tools and mentorship from industry leaders. By joining JP Morgan Chase in Mumbai, you will not only advance your career in a globally renowned firm but also play a crucial role in protecting millions of customers from fraud, contributing to the stability and integrity of the world's leading financial institution.

Key Responsibilities

• Develop and deploy AI/ML models to detect and prevent fraudulent activities in real-time across JP Morgan Chase's global operations
• Leverage graph-based analytics to identify complex fraud networks and patterns in transaction data
• Integrate large language models (LLMs) to enhance fraud detection through natural language processing of customer interactions and documents
• Collaborate with fraud risk teams to refine predictive models based on emerging threats in the financial services landscape
• Analyze large datasets from banking systems to uncover insights and improve model accuracy
• Conduct A/B testing and model validation to ensure robust performance in production environments
• Stay abreast of industry regulations and incorporate compliance requirements into data science solutions
• Mentor junior data scientists and contribute to the innovation roadmap for Fraud Data Science at JP Morgan Chase
• Present findings and recommendations to senior stakeholders to drive strategic fraud prevention initiatives

Required Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field; Master's degree preferred
• 2-4 years of experience in data science, machine learning, or predictive analytics, preferably in financial services or fraud detection
• Proficiency in Python or R for data analysis and modeling
• Strong understanding of machine learning algorithms and statistical methods
• Experience with large-scale data processing and SQL
• Knowledge of fraud risk management principles in the banking sector
• Ability to work collaboratively in a fast-paced, cross-functional team environment

Preferred Qualifications

• Experience with graph databases (e.g., Neo4j) and network analysis for fraud detection
• Familiarity with large language models (LLMs) and their applications in financial AI
• Advanced degree (Master's or PhD) in a quantitative discipline
• Prior work at a major financial institution like JP Morgan Chase or similar
• Certifications in data science (e.g., AWS Certified Machine Learning or Google Data Analytics)

Required Skills

• Machine Learning (supervised/unsupervised algorithms)
• Python programming (Pandas, Scikit-learn, TensorFlow)
• SQL and data querying for large financial datasets
• Graph analytics and network theory
• Large Language Models (LLMs) and NLP techniques
• Statistical analysis and hypothesis testing
• Big Data tools (Hadoop, Spark)
• Model deployment and MLOps practices
• Problem-solving and analytical thinking
• Communication and stakeholder presentation skills
• Fraud detection domain knowledge
• Regulatory compliance awareness (e.g., AML, KYC)
• Team collaboration and agile methodologies
• Data visualization (Tableau, Matplotlib)

Benefits

• Competitive base salary and performance-based bonuses aligned with JP Morgan Chase's global compensation structure
• Comprehensive health, dental, and vision insurance plans with employer contributions
• Retirement savings plan with company matching up to 6% of eligible compensation
• Generous paid time off, including vacation, sick leave, and parental leave policies
• Professional development opportunities through JP Morgan's internal training programs and tuition reimbursement
• Employee stock purchase plan and access to financial wellness resources
• Flexible work arrangements, including hybrid options in Mumbai, with modern office facilities
• Wellness programs featuring gym memberships, mental health support, and onsite health services

JP Morgan Chase is an equal opportunity employer.