Data Scientist Associate - Fraud Risk

JPMorganChase; Mumbai; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading financial institution in Mumbai seeks a Data Scientist Associate to join its Fraud Data Science team. The role involves developing advanced machine-learning models and graph analytics solutions to combat fraud. Candidates should have at least 3 years of experience in building production-quality models and strong technical skills in Python and big data platforms. A degree in a quantitative field is required, along with excellent problem-solving abilities. This position offers opportunities to innovate and positively impact the business.

Qualifications

• 3+ years of experience building and deploying production-quality machine-learning models.
• Strong technical skills in Python, PySpark, SQL and big-data/cloud platforms.
• Excellent problem-solving and communication skills.

Responsibilities

• Develop and implement advanced machine‑learning models for fraud detection.
• Build and maintain graph analytics solutions to uncover fraud patterns.
• Collaborate with teams to translate business needs into data-science solutions.

Skills

Machine Learning

Python

PySpark

SQL

Graph Analytics

Communication Skills

Education

Bachelor’s or Master’s degree in a quantitative field

Tools

AWS

Tableau

Job description

Join to apply for the Data Scientist Associate - Fraud Risk role at JPMorganChase

Join the Fraud Data Science team at JPMC and help drive innovation in fraud identification and prevention. As part of our team you will design, develop and deploy cutting‑edge AI/ML solutions—including graph analytics and large language models—to tackle complex fraud challenges and deliver measurable business impact.

Key Responsibilities

• Develop and implement advanced machine‑learning models (supervised and unsupervised) for fraud detection and prevention.
• Build and maintain graph analytics solutions to uncover fraud patterns and relationships.
• Leverage big data and cloud platforms (e.g., AWS, Spark) to automate, scale and productionalise analytical models and AI/ML tools.
• Collaborate with cross‑functional teams to translate business needs into actionable data‑science solutions.
• Present insights and recommendations to stakeholders, clearly communicating technical results and business impact.
• Document processes and ensure governance compliance for all analytical solutions.

Required Qualifications

• 3+ years of experience building and deploying production‑quality machine‑learning models.
• Hands‑on experience with supervised and unsupervised machine‑learning statistical models; knowledge of graph analytics is a big plus.
• Experience with large language models (LLMs) and agentic AI will be an added advantage; however, this is not mandatory.
• Strong technical skills in Python, PySpark, SQL and big‑data/cloud platforms.
• Familiarity with dashboarding tools (e.g., Tableau) and cloud services (AWS SageMaker, Amazon EMR).
• Excellent problem‑solving and communication skills – ability to convey complex findings clearly in both written and verbal form to technical and non‑technical audiences.
• Bachelor’s or Master’s degree in a quantitative field (mathematics, statistics, economics, computer science, engineering, etc.).

About Us

JPMorganChase is one of the oldest financial institutions, offering innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients. Our history spans over 200 years and today we are a leader in investment banking, consumer and small‑business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal‑opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender identity, sexual orientation, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.

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