Fraud Data Analyst

Wolfe•Pittsburgh, PA

9d•Onsite

About The Position

We are seeking a highly skilled Data Analyst who wants to accelerate their analytics career by working on high impact, real world problems at scale. This role focuses on building advanced reporting, automation, and data driven insights across large transactional datasets, where analysis directly influences business outcomes. The role supports fraud detection and risk related initiatives, but it is not a manual review, case investigation, or operations focused position. You will design dashboards, performance metrics, and alerting frameworks that measure system performance and surface meaningful patterns. Prior fraud experience is not required. Strong analytical thinking and technical skill matter most. This role is ideal for an analyst who enjoys complex data, scalable solutions, and applying advanced analytics or AI to practical business challenges. You will work closely with cross functional partners to turn insights into measurable improvements. This is a 5-day onsite role in Pittsburgh, PA.

Requirements

At least 4 years of experience as a Data Analyst working with complex or high volume datasets.
Strong SQL skills and proficiency in Python, including pandas and related analytics libraries. Experience with Spark or PySpark for large scale data processing is a plus
Experience building dashboards and performance reporting using BI tools such as Tableau, Metabase, or similar platforms.
Experience designing analytics solutions that support operational, risk, or performance related decision making. Prior fraud, risk, or compliance domain experience is helpful but not required.
Exposure to automation, workflows, or orchestration tools such as Airflow, and familiarity with advanced analytics or AI driven applications.
Ability to translate analytical findings into clear insights and collaborate effectively with cross functional partners.

Responsibilities

Analytics and Reporting: Develop and maintain dashboards and reports that measure performance, identify trends, and support data driven decision making across large transactional datasets.
Ongoing Pattern and Anomaly Analysis: Analyze high volume data to identify meaningful patterns, anomalies, and emerging risks, and translate findings into clear insights for stakeholders.
Automation and Alerting: Design and improve automated workflows, rules, and alerting frameworks that surface issues early and reduce reliance on manual analysis.
Advanced Analytics and AI: Apply advanced analytics, statistical methods, or AI-driven techniques to improve monitoring, detection, and performance measurement in targeted areas.
Cross Functional Collaboration: Partner with product, engineering, operations, and other teams to align analytics solutions with business goals and support measurable improvements.

Benefits

Incentive Bonus
Restricted Stock Units (RSUs)
Profit Share
Medical, Prescription, Vision, and Dental insurance for employees and dependents (Wolfe pays 80% of premium)
Short-Term Disability Insurance (Wolfe pays 100% of premium)
Voluntary Long-Term Disability Insurance, Life Insurance, Critical Illness Insurance, Accident Insurance, and Hospital Indemnity coverage
PTO (vacation and sick time)
Corporate Holidays and Floating Holidays
401(k)
Employee recognition program
Charitable Donation to a charity of your choice yearly
Employee Referral Bonus
Tuition Reimbursement
Internal Training and Information sessions
Family Picnic, Holiday Party, and other outings
Internal Culture Club