Quantitative Analytics Analyst - Fraud Prevention and Risk Management

Quant Analytics Analyst

 

Quantitative Analytics Analyst on our Consumer and Community Banking Fraud Prevention Optimization Strategy team to reduce cost of fraud and improving customer experience. The breadth of experiences, learnings, and connections in this role will enable your growth and development. To excel, you'll be highly motivated, highly analytical, extremely detail oriented, and an exceptional problem solver who takes pride in being part of an organization that owns customer issues from beginning to end and delivers accurate, timely solutions. 

 

As a member of the Fraud Prevention Optimization team, you will focus on reducing cost of fraud, through complex analyses combined with business insights and collaboration.

 

Job Responsibilities

• Interpret and analyze complex data to formulate problem statement, provide concise conclusions regarding underlying risk dynamics, trends, and opportunities.
• Use advanced analytical & mathematical techniques to solve complex business problems. 
• Manage, develop, communicate, and implement optimal fraud strategies to reduce fraud related losses and improve customer experience across credit card fraud lifecycle. 
• Identify key risk indicators, develop key metrics, enhance reporting, and identify new areas of analytic focus to constantly challenge current business practices.
• Provide key data insights and performance to business partners.
• Collaborate with cross-functional partners to solve key business challenges.
• Assist team efforts in the critical projects while providing clear/concise oral and written communication across various functions and levels.
• Champion the usage of latest technology and tools, such as large language models, to drive value at scale across business organizations.

 

Required qualifications, capabilities, and skills

• Bachelor’s degree in a quantitative field or 1 year risk management or other quantitative experience
• Background in Engineering, statistics, mathematics, or another quantitative field 
• Advanced understanding of Python, SAS or SQL
• Query large amounts of data and transform into actionable recommendations.
• Strong analytical and problem-solving abilities
• Experience delivering recommendations to leadership
• Self-starter with ability to execute quickly and effectively.
• Strong communication and interpersonal skills with ability to interact with individuals across departments/functions

 

Preferred qualifications, capabilities, and skills

• MS degree in a quantitative field or 2 or more years risk management or other quantitative experience.
• Hands on Knowledge of AWS and Snowflake.
• Advanced analytical techniques like Machine Learning, Large Language Model Prompting or Natural Language Processing will be an added advantage.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. 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 at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, 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. Visit our FAQs for more information about requesting an accommodation.

Experience Level

Senior Level