Senior Fraud Strategist

RealPage, Inc.•Richardson, TX

7d•$94,700 - $161,300•Remote

About The Position

The Senior Fraud Strategist is responsible for developing, testing, and optimizing fraud strategies, policies, rules, thresholds, treatment paths, and decision logic within assigned onboarding and monitoring workflows in RealPage’s payments ecosystem. This role will focus on development of policies and rules across new account onboarding, tenant payments, vendor payments, owner draws, funding instrument verifications, limit management, transaction monitoring, and payer anomalies. The successful candidate will take part in building RealPage’s next generation of fraud controls. This is a hands-on strategy role for someone who can independently identify the right data, write and troubleshoot SQL, connect fraud signals across systems, and translate analysis into practical decisions. They will test hypotheses, quantify fraud exposure and customer impact, evaluate strategy performance, and recommend policies, rules, thresholds, and controls that reduce fraud while protecting the customer experience and enabling business growth.

Requirements

Bachelor’s degree in Data Science, Analytics, Statistics, Finance, Economics, Risk Management, Criminal Justice, Computer Science, or related field, or equivalent practical experience.
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.
Advanced, hands-on SQL experience is mandatory. Candidates must be able to independently write, troubleshoot, and explain SQL queries used to source data, validate hypotheses, identify fraud patterns, assess false positives, and evaluate rule or control performance; dashboard-only experience is not sufficient for this role.
Demonstrated experience developing or optimizing fraud rules, thresholds, decision logic, treatment paths, controls, or monitoring strategies based on independently sourced and analyzed data.
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.
Advanced analytical curiosity and ability to connect fraud signals across disconnected tools, imperfect data, evolving processes, and multiple product or payment workflows.
Strong ability to translate independently sourced data findings into clear fraud strategy recommendations, rule changes, threshold adjustments, control improvements, monitoring plans, and policy considerations.
Strong 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, refund or dispute abuse, 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.

Nice To Haves

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.

Responsibilities

Responsible for the development, maintenance, and optimization of fraud risk policies, strategies, rules, thresholds, decision logic, treatment paths, and control documentation across onboarding and monitoring workflows.
Develop data-backed recommendations for auto-approval criteria, manual-review routing, payment holds, restrictions, limit treatments, step-up verification, account monitoring, and escalation thresholds.
Document strategy rationale, rule logic, data sources, expected impact, monitoring plans, policy considerations, change history, and recommended follow-up actions.
Design 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, refund or dispute abuse, and emerging typologies.
Monitor launched strategies and recommend tuning on an ongoing basis.
Independently source, query, and analyze data using SQL to validate hypotheses, identify fraud patterns, assess false positives and false negatives, and evaluate loss exposure, operational impact, and customer friction.
Write and troubleshoot SQL queries using multi-table joins, aggregations, date windows, common table expressions, window functions, and segmentation logic to investigate fraud patterns and measure strategy performance.
Apply analytical and data science methods to support feature exploration, cohort analysis, segmentation, model output evaluation, threshold setting, experimentation, champion/challenger comparisons, back-testing, and post-launch 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; assess and provide feedback on whether those outputs are effective for fraud strategy use cases, with guidance on complex cases.
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.
Share fraud findings and trends with fraud operations, monitoring, and escalation teams to inform how case learnings translate into policies, rules, thresholds, or monitoring improvements.