Fraud Data Analyst

The Fraud Strategy Analyst is responsible for supporting the development, testing, and ongoing optimization of fraud strategies, policies, rules, thresholds, and decision logic across RealPage’s payments ecosystem. This role will focus on fraud prevention and detection across new account onboarding, tenant payments, vendor payments, owner draws, funding instruments, limit management, and payout activity.

This is a hands-on, technical role for a fraud professional with strong analytical skills, data science exposure, and mandatory SQL experience. The ideal candidate can query data independently, identify fraud patterns, test hypotheses, evaluate strategy performance, and translate findings into practical fraud controls while balancing risk mitigation, customer experience, operational workload, and business growth.

Fraud Strategy, Policy & Controls 

• Support development and maintenance of fraud risk policies, strategies, rules, thresholds, decision logic, treatment paths, and control documentation across onboarding and monitoring workflows.
• Help build and optimize controls for payment fraud, onboarding risk, account takeover, business email compromise, counterparty fraud, tenant payment fraud, synthetic identity, first-party misuse, bust-out behavior, stolen payment instruments, and emerging typologies.
• Document strategy rationale, rule logic, expected impact, monitoring plans, policy considerations, change history, and recommended follow-up actions Analytics, Data Science & Rule Performance
• Use SQL to independently query data, validate hypotheses, identify fraud patterns, assess false positives, and evaluate loss exposure, operational impact, and customer friction.
• Apply analytical and data science methods to support feature exploration, segmentation, model output evaluation, threshold setting, experimentation, champion/challenger comparisons, and performance monitoring.
• Partner with Risk Data Science & Analytics to translate dashboards, models, features, risk scores, and analytical insights into practical fraud decision strategies and operational controls.

Operational Feedback & Cross-Functional Execution

• Partner with Onboarding Risk Operations and Risk Monitoring Operations to incorporate case outcomes, queue trends, investigator feedback, alert quality, and operational pain points into strategy improvements.
• Review themes from Trust and Safety escalations to identify control gaps, recurring fraud signals, product or process vulnerabilities, or policy needs requiring durable remediation. 
• Collaborate with Product, Engineering, Payment Operations, Compliance/AML, Legal, and Operational Excellence on tooling, workflow, data availability, rule implementation, and control monitoring.
• Provide concise updates on fraud trends, strategy performance, emerging risks, rule effectiveness, false positive impact, and recommended actions to fraud leadership and cross-functional stakeholders.

Required:

• 3-5 years of full-time experience in fraud strategy, fraud analytics, payments risk, data science, financial crime, risk operations strategy, or a related technical risk function
• Mandatory SQL experience, with the ability to independently query data, validate hypotheses, assess rule or control performance, and support fraud strategy development.
• Exposure to data science, statistics, experimentation, model evaluation, Python/R, feature development, segmentation, or analytical methods used in fraud or risk decisioning.
• Experience working with fraud operations, risk analytics, data science, product, engineering, compliance, or payment operations stakeholders.
• Bachelor’s degree in Data Science, Analytics, Statistics, Finance, Economics, Risk Management, Criminal Justice, Computer Science, or related field, or equivalent practical experience.

KNOWLEDGE/SKILLS/ABILITIES 

Required: 

• Strong analytical curiosity and ability to connect fraud signals across disconnected tools, imperfect data, and evolving processes.
• Ability to translate data findings into clear fraud strategy recommendations, rule changes, control improvements, and policy considerations.
• Working knowledge of fraud typologies such as synthetic identity, first-party misuse, counterparty fraud, business email compromise, onboarding fraud, stolen payment instruments, tenant payment fraud, account takeover, or bust-out behavior.
• Ability to evaluate fraud strategies using metrics such as loss exposure, fraud capture, precision, false positives, customer friction, queue impact, and post-launch performance trends.
• Strong written and verbal communication skills, including the ability to summarize technical findings for fraud, product, operations, data science, and leadership audiences.
• High ownership, sound judgment, attention to detail, and ability to balance fraud mitigation with customer experience, operational capacity, compliance considerations, and business growth.
• Preferred experience with property management, rent payments, real estate technology, B2B payments, vendor payments, bill pay, embedded payments, merchant acquiring, fraud platforms, payment processor portals, device/identity signals, or decisioning platforms such as Oscilar.

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Physical Demands and Working Conditions

While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to finger, handle or feel objects, tools or controls; reach with hands and arms; climb stairs; talk or hear. The employee must have the ability to operate a personal computer and express or exchange ideas by means of the spoken word. May be required to sit and/or stand for long periods of time. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. May be required to lift or move 10+ pounds.