Quant Analytics Associate I - Fraud Strategy

Drive impactful fraud prevention as a Quantitative Analytics Associate on our Point of Sale Fraud team - where your advanced risk analyses and strategic insights help reduce fraud losses, protect customers, and influence key decisions across the organization. As a Quantitative Analytics Associate in the Point of Sale Fraud team, you will manage fraud risk strategies in the Fraud Policy area and perform complex risk analyses with the objective of reducing fraud related losses while balancing customer impact. You will frequently interact with cross‑functional partners and present findings to managers and executives. Job 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 Required Qualifications Bachelor's degree (or related work experience) in a quantitative discipline in a financial services organization and 2 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 Qualifications Master's degree (or related work experience) in a quantitative discipline, preferably in a financial services organization, plus 2 or more years' experience in fraud/risk/payments or related field. Experience with Machine Learning technologies and knowledge of LLMs. Benefits We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, including comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Equal Opportunity Employer 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, 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. #J-18808-Ljbffr