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 fieldor 1year 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 fieldor 2or 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.
