Overview 

Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment experience. It’s hard to believe that it’s 2024 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! Flex enables our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing. Will you be a part of the team?

About the role

As a Decision Scientist you’ll be part of the Fraud Risk team responsible for managing fraud and abuse risk with KPIs of balancing fraud loss metrics and customer experience. You will be tasked to set fraud risk management goals, design, deploy and manage fraud risk policy & strategy as well user experience by closely collaborating with product, eng, compliance and other business stakeholders. As a fraud domain owner, you’ll partner closely with Finance, Analytics and leadership to identify insights, create roadmaps and drive down fraud losses to maximize LTV. 

What you’ll do

• Maintain and further refine the fraud strategy framework, including fraud model strategies and flash fraud surgical rules
• Build and refine fraud model strategy automation process to keep the model strategy up-to-date with high performance
• Detect anomalies and fraud trends, write risk rules targeting fraud patterns and closely monitor the solution performance.
• Review cases daily to timely capture flash fraud trends with quick response to stop loss leakage
• Swiftly respond to system issues and deep dive into root cause analysis
• Master large volumes of data; extract and manipulate large datasets using standard tools such as SQL and Python
• Work closely with our vendors to optimize their performance
• Become an expert on data sources and a thought leader in fraud risk

Key qualifications

• Bachelor's degree is in Statistics or an equivalent quantitative field
• 5 years fraud analytics experience
• Experience in data mining and analysis tools such as Python/ SQL etc
• Good communication skills and the ability to understand and synthesize requirements across multiple project domains
• Passionate about solving problems with data and a high level of intellectual curiosity
• Highly motivated to work on multiple projects and a team player with a startup spirit

The national pay range for this role is $130,000-$170,000 in base salary. Individual compensation will be commensurate with the candidate's experience aligned with Flex's internal leveling guidelines and benchmarks.