Senior Staff, Decision Scientist, Fraud Policy

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 2026 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 Senior Staff Decision Scientist on the Risk team, you will own the strategy, design, and optimization of Flex's fraud and account-security decisioning stack. You'll set policy across the customer lifecycle — onboarding, identity, transaction, and account takeover — balancing fraud loss, customer experience, and growth across millions of transactions. This is a senior individual-contributor role. You will be the policy voice in the room, setting direction for how Flex detects and prevents fraud, and working across Risk, Product, Engineering, Compliance, and Data to ship and measure that policy in production. What You'll Do Own and evolve Flex's fraud-prevention and account-security policy across onboarding, identity/KYC, payments, and account-takeover surfaces Design, ship, and tune detection rules and decisioning logic in the risk decision engine — from signal definition to live rollout Use large-scale transaction, identity, and behavioral data to identify emerging fraud patterns and quantify their loss impact Build models and forecasts to size the fraud/loss and customer-experience tradeoffs of every policy change before it ships Design shadow tests and experiments, and measure the tradeoff between fraud loss, false-positive friction, and approval/growth Set the fraud-loss and dispute/chargeback strategy, and define what "good" looks like across the detection portfolio Define the metrics, monitoring, and dashboards that keep fraud performance observable and catch regressions early Partner closely with Product, Engineering, Compliance, and Operations to take policy from analysis to production impact Communicate clear, actionable recommendations — and the risk tradeoffs behind them — to leadership and stakeholders What We're Looking For 8+ years in fraud, risk, decision science, or platform analytics, with deep experience owning fraud or risk policy end-to-end Strong hands-on skills in Python and SQL, and comfort working with large, messy transactional datasets Experience with fraud and risk concepts — rule/policy design, loss modeling, cohort analysis, and precision/recall tradeoffs Track record building or operating detection systems on high-scale transactional platforms (payments, lending, marketplaces) Fluency with fraud signals and typologies: identity/KYC, account takeover, first-party fraud, payment fraud, and disputes/chargebacks Strong product and business intuition — you care about shipping impact and reducing loss, not just analysis Comfortable operating cross-functionally and owning ambiguous, high-leverage problem spaces Background in fintech, payments, or large tech platforms is a strong plus Compensation Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be commensurate with their experience, qualifications, and Flex’s internal leveling guidelines and benchmarks. Tier 1 (NYC/Bay Area, Los Angeles, Seattle) $190,000 — $235,000 USD Tier 2 (Austin, Washington D.C. Philadelphia, San Diego, Chicago, Atlanta) $172,000 — $215,000 USD Tier 3 (Salt Lake City, all other USA cities) $160,000 — $204,000 U…