This role pays more than
57%
of similar roles. Most pay
$176,450–$241,750
— the shaded band above.
At the midpoint, this role pays about
$220k
versus about
$209k
for comparable roles.
Based on 240 similar postings.
Employer
About Intuit
Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology
Intuit currently has
210 open roles
on FindRole.
Listed pay typically runs
$202,500–$274,000
across 187 roles with salary data.
Staff Product Manager, Bill Pay and Payroll Transaction Risk joins the team to own the strategy and outcomes for bill payment and payroll transaction risk. This role is accountable for hitting fiscal-year goals regarding loss reduction and insult-rate reduction by managing risk decisioning approaches, data science models, and counterparty risk signals. The successful candidate will evaluate and operationalize new data vendors, develop features to assess payee and contractor risk, and advance real-time, AI-native decisioning while monitoring latency and explainability. Key requirements include technical fluency in APIs, data infrastructure, and streaming decisioning, alongside experience with ML models, precision/recall trade-offs, and A/B testing. The work involves solving the technical challenge of balancing real-time fraud prevention with the need for seamless, accurate money movement for small businesses.
What does a Product Manager earn in New York?
Median $195400 from 268 postings across 43 companies.
Set and deliver the strategy to achieve fiscal year goals for loss reduction and false-positive rate reduction.
Define the risk decisioning strategy by combining models, rules, and signals to approve good transactions and stop fraud.
Evaluate, integrate, and operationalize new data vendors and internal sources to improve decision accuracy.
Develop features and signals to assess the risk of transaction counterparties and their relationships.
Advance real-time, AI-native decisioning systems focusing on latency, reliability, and explainability.
Instrument and report key metrics including loss rates, model precision, recall, and decision latency to leadership.
Prioritize and manage delivery timelines across data science, engineering, risk policy, compliance, and operations teams.
What we're looking for
4+ years in Product Management, including sustained ownership of complex, technical, multi-team initiatives with accountability for measurable business outcomes.
Proven track record building risk/fraud decisioning strategies with ownership of loss and/or false-positive outcomes.
Deep partnership with data science/ML teams to develop, evaluate, and productionize models.
Experience with data vendors and data pipelines for evaluating and operationalizing third-party and internal data.
Strong technical fluency in real-time/streaming decisioning, APIs, data infrastructure, and experimentation.
Quantitative rigor with analytics and A/B testing to size opportunities and prove impact.
Experience in payments, fraud, risk, or another high-scale financial domain.
Bachelor's degree required; Master's degree or MBA preferred.