Senior Director of Decision Analytics

Payactiv•Milpitas, CA

2d•Onsite

About The Position

We are Payactiv, a FinTech company in the heart of Silicon Valley, devoted to giving workers access to their earned wages when they need them. Payactiv is the pioneer and industry leader in Earned Wage Access. We are the only Certified B Corporation and Public Benefit Corporation in our industry. Our app provides millions with financial services that help them avoid debt, manage their finances, and regain flexibility to pay for things on their own schedule. As Payactiv expands its product offerings to serve workers throughout the U.S., the Decision Analytics team is seeking a Senior Director of Decision Analytics, based out of our Milpitas office, to further build out and lead the decision analytics function behind our product offerings. This is a high-visibility leadership role for a proven risk leader who has scaled risk analytics at a consumer fintech and is passionate about expanding financial access. The Decision Analytics team is responsible for building the data-driven intelligence that powers many of Payactiv’s financial products and business decisions. We develop forecasting models, decision engines, risk strategies and other analytical solutions that help drive business performance at scale. Working closely with Product, Engineering, Operations, Finance and other stakeholders, we turn data into actionable insights and automated decisions that improve customer outcomes, strengthen partner relationships, and support long-term growth.

Requirements

Bachelor’s degree in a quantitative discipline – Data Science, Statistics, Mathematics, Economics, Engineering, etc.; advanced degree preferred.
8+ years of experience in consumer credit risk, risk analytics, or decision science, including 3+ years building and leading analytical teams.
Direct experience owning risk at a consumer fintech — earned wage access, cash advance, BNPL, or near-prime consumer lending (e.g., EarnIn, Dave, Brigit, MoneyLion, Affirm, Klarna) — strongly preferred.
A proven track record of owning risk decision strategy and loss outcomes at scale, including experience serving U.S. workers — with deep fluency in loss forecasting, portfolio management, unit economics, and experimentation, and the ability to connect risk decisions directly to P&L outcomes.
Hands-on experience debiting consumer financial instruments at scale across methods — ACH debits (standard and same-day), merchant-initiated debits of debit and prepaid cards via payment networks (e.g., Visa, Mastercard), and emerging real-time rails (RTP, FedNow) — including debit timing, sequencing, and retry strategies, and managing returns, NSF, chargebacks, and disputes.
Hands-on technical depth in SQL and Python, with working knowledge of modern ML approaches to risk modeling (e.g., gradient boosting frameworks) — credible going deep with your team.
Executive-level communication skills — able to distill complex risk trade-offs for C-suite and board audiences and influence decisions across functions.

Nice To Haves

Working knowledge of U.S. payment rails and the rules that govern consumer debits (e.g., Nacha operating rules, Regulation E), and of the broader regulatory landscape for earned wage access and consumer credit, is a strong plus.

Responsibilities

Define and own the risk decision strategy for Payactiv’s product offerings — partnering with executive leadership to strike the right balance between expanding access, growth, and loss performance.
Own end-to-end risk decisioning strategy: eligibility criteria, advance limits, repayment risk models, debit and recovery strategies, and portfolio management — from initial design through deployment, monitoring, and iteration.
Build loss forecasting, vintage and cohort analysis, and unit-economics frameworks; own portfolio metrics such as approval rates, loss rates, repayment performance, and risk-adjusted profitability, and report on them to executive leadership.
Build, lead, and mentor a high-performing team of risk data scientists and analysts — setting the bar for technical rigor, speed, and business impact.
Champion a test-and-learn culture — design, run, and read experiments that expand access to more workers while holding losses within appetite.
Establish model governance standards — documentation, validation, performance monitoring, and controls that keep pace with regulatory expectations.
Act as a trusted advisor to Product, Engineering, Finance, Compliance, and executive stakeholders, translating complex analyses into clear decisions; partner with fraud and identity teams where risk domains intersect.