Quant Analytics Associate I - Fraud Strategy

Fairygodboss; Wilmington (DE); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Comprehensive health care coverage

Retirement savings plan

Tuition reimbursement

Job summary

Fairygodboss in Wilmington, Delaware, is seeking a Quantitative Analytics Associate for its Point of Sale Fraud team. This role involves managing fraud risk strategies, conducting complex analyses, and collaborating with various partners to protect customers and reduce fraud losses.

The ideal candidate will have a bachelor's degree in a quantitative discipline and at least 2 years of experience in fraud or risk analysis. Strong skills in Python, SAS, and SQL, along with the ability to interpret large datasets, are essential for success in this role.

Qualifications

• 2+ years of experience in fraud/risk/payments or related field.
• Ability to query large datasets and provide actionable insights.
• Self-starter with strong communication skills.

Responsibilities

• Interpret complex data to identify risks and trends.
• Manage fraud strategies to reduce losses.
• Collaborate with partners on key challenges.

Skills

Python

SAS

SQL

Analytical skills

Problem-solving abilities

Communication skills

Education

Bachelor's degree in a quantitative discipline

Master's degree in a quantitative discipline

Tools

Data mining tools

Machine Learning technologies

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 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.