Technical Product Manager, Quantifind
Core Models
$145-185k
+ Equity
Office located in Palo Alto, CA
Automated AML investigations
Be an early applicant
Automated AML investigations
21-100 employees
Be an early applicant
$145-185k
+ Equity
Office located in Palo Alto, CA
21-100 employees
Company mission
To help customers leverage powerful AI and disruptive science to automatically discover hidden criminal and financial risk.
Role
Who you are
- You are a highly analytical professional that operates at the interface of Product Management and Data Science
- You understand that a model’s value depends only on how well it solves a real customer problem
- You can translate a use case into a clear prediction target, define what constitutes a true positive, and reason through the tradeoffs between missed risk and unnecessary alerts
- You are comfortable discussing precision, recall, and ROC analysis with data scientists, and explaining what those metrics mean to customers
- You are drawn to the intersection of product strategy and applied machine learning
- You know how to turn customer needs into model requirements, evaluate whether an improvement matters in practice, and prioritize new capabilities alongside improvements to existing models
- You are rigorous and analytical, but you move with urgency and make practical decisions with imperfect information
- You are collaborative by nature and have achieved success as a team player
- You thrive by setting ambitious goals and tracking progress until they are met
- You feel strongly about being mission-driven in your work, and above all else you are innately curious and motivated to learn new things
- BS or MS in computer science, statistics, mathematics, engineering, or a related technical field, or bring equivalent practical experience
- 2+ years of product management, data science, and/or data analytics experience working with software powered by machine learning models or with significant model-driven capabilities
- You have a strong working command of classifier performance metrics, including precision, recall, false-positive and false-negative rates, and ROC analysis and can interpret evaluation results, explain threshold tradeoffs, and connect those tradeoffs to customer outcomes
- You can turn an ambiguous customer problem into a well-defined model use case, prediction target, and measurable acceptance criteria
- You understand how label quality, class imbalance, and the representativeness of evaluation data affect conclusions about model performance
- You are comfortable partnering closely with Data Science and Engineering, distinguishing product decisions from modeling implementation choices while contributing meaningfully to both discussions
- You communicate clearly with technical and nontechnical audiences and can explain model capabilities and limitations without overstating what the evidence supports
- You understand agile software development and can translate priorities into clear requirements and an actionable backlog
- You have an ownership mentality, thrive in ambiguity, and build alignment by clearly communicating the “why” and driving toward measurable outcomes
- Bonus: You bring familiarity with natural language processing, experience with financial crime or risk intelligence products, or exposure to model validation and Model Risk Management in regulated institutions
What the job involves
- As Technical Product Manager for Core Models, you will own the product direction for the models that power Graphyte’s risk intelligence. This role is co-sponsored by our Data Science organization. You will work closely with Product, Data Science, and Engineering to determine which model capabilities to build, where to improve existing models, and how to measure success
- Own the Core Models product strategy and roadmap- Prioritize model build and refresh initiatives based on customer needs, performance gaps, business value, and technical feasibility
- Translate use cases into clear model objectives- Define prediction targets, what constitutes a true positive, and the performance requirements that reflect how customers use the results
- Guide model evaluation and threshold selection- Partner with Data Science to establish evaluation criteria and select thresholds that balance precision, recall, missed risk, and review workload for the intended use case
- Drive model initiatives through delivery- Define scope, requirements, acceptance criteria, and release priorities; align Data Science and Engineering on execution; and assess results against the intended product outcomes
- Guide ongoing model improvement- Use evaluation results, customer feedback, and performance monitoring to identify gaps and prioritize refreshes or further development
- Co-own customer-facing model documentation with Data Science- Clearly explain intended uses, evaluation methods, performance, assumptions, limitations, and material changes
- Serve as a customer-facing subject matter expert on our models- Support technical discussions, evaluations, and customer reviews, translating model behavior and performance into clear, defensible explanations
- Own Quantifind’s interfaces with customer Model Risk Management processes- Coordinate model questionnaires, validation requests, supporting documentation, and responses to findings in partnership with Data Science and other internal stakeholders
- Work directly with executive leadership as you help us innovate new solutions
- Our team of highly innovative data scientists and engineers will challenge you to validate assumptions, identify new opportunities, and become an expert on our product and customers. You will have direct client exposure, with the expectation that great product insights come from user feedback. Principally, you will become part of a motivated and curious product team on a journey to create the world’s premier risk intelligence platform
Our take
The global cost of money laundering stands in the trillions of dollars, with related fines costing businesses billions a year. Quantifind aims to help combat this with automated risk decisions and anti-money laundering investigations, freeing up clients' security teams to focus on the biggest threats.
Quantifind's AI-driven "Graphyte" platform encompasses GraphyteSearch, a web-based investigation application, plus GraphyteAPI for integration, and GraphyteBatch that enables users to submit large numbers of queries at once. Altogether, this allows the platform to act as a one-stop shop for AML, delivering value across the whole risk mitigation process.
At the end of 2022, Quantifind was named one of the most innovative companies in the industry by Fintech Global, after signing 4 of the largest banks in the world, showing the impressively high regard in which its solutions are held. It received $23 million in funding in 2023 to expand its international presence, grow brand recognition, and continue to enhance its offerings.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
Jun 2026
$200m
LATE VC
Jan 2025
$22m
LATE VC
Total funding: $313.3m
Company benefits
- Meaningful equity to full-time employees
- Performance reviews conducted twice per year, with opportunities to advance
- Collaboration across departments - there’s always an opportunity to work on the projects you care most about
- Flexible hours and a flexible vacation policy
- Remote or in-office options
- We encourage people to hone their crafts by taking classes and attending conferences
- We pay 95% of your premiums with top medical, dental and vision plans for you and your family, plus other benefits including FSAs and life insurance
- We match employee retirement contributions dollar-for-dollar up to 4% after your first year
Company HQ
Downtown North, Palo Alto, CA
Leadership
Ari Tuchman
(Co-Founder & CEO)Founder and Chairman of Entanglement Technologies. Former Research Scientist at Stanford.
John Stockton
(Co-Founder)Has worked as a Physicist at Entanglement Technologies, and was a Postdoc at Stanford.
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