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Quant Analytics Associate Senior - Fraud Strategy

J.P. Morgan

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

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 II 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 and communicate with cross-functional partners and communicate and present presentations 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, capabilities, and skills

  • 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 qualifications, capabilities, and skills

  • 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.

This role is not eligible for visa sponsorship

ABOUT US

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

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, based on eligibility. These benefits include 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. Additional details about total compensation and benefits will be provided during the hiring process. 

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.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

Vacancy posted 9 days ago
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