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Chase · 4 months ago

Quant Analytics Associate II - Fraud Strategy

1111 Polaris Pkwy, Columbus, OH, 43240, US

Full-time

Onsite

Mid Level

3+ years exp

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. As a Quantitative Analytics Associate II on the Point of Sale Fraud team, you will manage fraud risk strategies and perform complex risk analyses to reduce fraud losses while enhancing customer experience. The role involves collaborating with cross-functional partners and presenting findings to management.

BankingFinancial Services

Responsibilities

Interpret large amounts of complex data to formulate problem statement, concise conclusions regarding underlying risk dynamics, trends, and opportunities

Manage, develop, communicate, and implement optimal fraud strategies (including rules, cutoffs, policies, operational flows, etc.) to protect the bank from fraud related losses and improve customer experience at Point of Sale

Identify key risk indicators and metrics, develop key metrics, enhance reporting, and identify new areas of analytic focus to better capture fraud

Provide subject matter expertise on strategy implementation/testing and initiatives related to the improvement of risk mitigation processes and infrastructure

Collaborate with cross-functional partners to understand and address key business challenges

Identify business opportunity by performing well thought analysis – Data mining, ensuring data integrity, synthesizing and communicating findings to senior management

Assist team efforts in the critical development of new fraud pattern or spending pattern detection tools while providing clear/concise oral and written communication across various functions and levels, inclusive of Operations, IT, and Risk Management

Qualification

PythonSASSQLData analysisMachine LearningCommunication skillsProblem-solvingInterpersonal skillsSelf-starter

Required

Bachelor's degree (or related work experience) in a quantitative discipline in a financial services organization, plus 3 or more years' experience in fraud/risk/payments or related field

Advanced understanding of Python, SAS, and SQL

Ability to query large amounts of data and transform raw data into actionable management information

Strong analytical and problem-solving abilities

Experience delivering recommendations to management

Self-starter with the ability to drive for resolution

Strong communication and interpersonal skills with the ability to interact with individuals across departments/functions and with senior-level executives

Preferred

Master's degree (or related work experience) in a quantitative discipline, preferably in a financial services organization, plus 3 or more years' experience in fraud/risk/payments or related field

Experience with Machine Learning technologies. Knowledge of LLMs