Join our dynamic team as a Quantitative Analytics Associate on the Consumer and Community Banking Fraud Prevention Optimization Strategy team. This role offers a chance to reduce fraud costs and enhance customer experience through complex analyses and collaboration. You'll be part of a team that leverages advanced analytics and innovative tools to promote impactful business improvements, while interacting with cross-functional partners and presenting insights to leadership.
Job Summary
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 3years risk management or other quantitative experience
- Background in Engineering, statistics, mathematics, or another quantitative field
- Advanced understanding of Python, SAS, and 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 and with senior level executives
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.
