Director, Risk, Data Science and Analytics
About The Position
We are seeking a visionary and hands-on Risk Data Science and Analytics Leader to architect the next generation of risk intelligence for a dynamic payments platform serving the property management industry. This role will lead the development of advanced risk models and AI-powered systems across fraud, compliance, and credit domains—while also driving real-time, adaptive decisioning that balances protection with growth. You will spearhead the use of AI agents and real-time risk scoring to automate underwriting and fraud review, while leveraging internal and external data to deliver personalized financial experiences . These include dynamic transaction and velocity limits, accelerated payment flows for low-risk users, and risk-based upselling and cross-selling strategies. By embedding intelligent risk insights into every customer touchpoint, you will help the business increase approvals, reduce friction, and unlock new revenue opportunities—all while maintaining a secure and compliant ecosystem.
Requirements
- Advanced degree in Data Science, Statistics, Economics, Computer Science, or a related field.
- 10+ years of experience in risk analytics, preferably in payments, fintech, or financial services.
- Proven track record of building and deploying risk models and AI solutions in production.
- Strong proficiency in Python, SQL, and machine learning frameworks.
- Experience with fraud detection systems, anomaly detection, and behavioral modeling.
- Hands-on experience with LLMs, NLP, and agentic workflows for operational automation.
- Experience developing composite risk scores using multi-dimensional data sources.
- Strong business acumen and ability to translate risk insights into growth strategies.
- Excellent communication skills and ability to influence cross-functional stakeholders.
Responsibilities
- Risk Model Development and Maintenance Design, build, and maintain predictive models for fraud detection, credit risk assessment, and compliance monitoring.
- Develop and maintain enterprise risk scores for tenants and property managers, integrating multi-dimensional signals from compliance, fraud, and credit risk profiles.
- Build real-time fraud risk scoring systems using behavioral analytics, device intelligence, identity verification, and transaction anomaly detection.
- Loss Forecasting and Reporting Develop robust forecasting frameworks for credit and fraud losses.
- Deliver accurate and timely reporting to finance, operations, and executive leadership.
- Monitor portfolio performance and identify emerging risk trends, including fraud typologies and attack vectors.
- Experimentation and Policy Simulation Lead A/B testing and simulation efforts to evaluate new risk policies and operational strategies.
- Quantify trade-offs between fraud prevention, credit exposure, and customer experience.
- Partner with policy and product teams to iterate on risk rules, thresholds, and fraud mitigation strategies.
- Workforce Modeling and Productivity Reporting Build models to forecast operational headcount needs based on transaction volumes, risk profiles, and policy changes.
- Develop dashboards and reporting tools to track team productivity and efficiency.
- Support workforce planning and budget allocation with data-driven insights.
- Workflow Automation Collaborate with strategic partners, product, and engineering teams to design and implement AI agents to automate manual underwriting and fraud review workflows.
- Leverage natural language processing (NLP), large language models (LLMs), and decision intelligence to streamline document analysis, customer evaluation, and exception handling.
- Build intelligent agents capable of triaging fraud alerts, escalating high-risk cases, and learning from feedback loops.
- Real-Time Risk Decisioning Partner with product and engineering to develop dynamic, real-time risk decisioning systems that adapt to user behavior, transaction context, and external signals.
- Integrate internal data (e.g., payment history, behavioral patterns) and external data (e.g., credit bureaus, identity verification, device intelligence) to power customized offerings such as:
- Payments acceleration for low-risk users
- Dynamic transaction and velocity limits based on real-time risk posture
- Risk-based pricing, upselling, and cross-selling of financial products
- Collaborate with product, marketing, and revenue teams to embed risk intelligence into customer journeys and lifecycle strategies.
Benefits
- Health, dental, and vision insurance.
- Retirement savings plan with company match.
- Paid time off and holidays.
- Professional development opportunities.
- Performance-based bonus based on position.
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What This Job Offers
Job Type
Full-time
Career Level
Director
Number of Employees
1,001-5,000 employees
