Samaya AI

Product Manager - Finance

New York, New York, United States · Senior

H1B sponsorship available$140k-$210kDetected 29 days ago

PythonSQLDatabricksMachine LearningData AnalysisLLMsAgentic AIA/B TestingFinancial ModelingFinancial AnalysisValuationResearchCommunication

About the role

You'll be the bridge between our Product, ML Research, and Engineering teams: defining real-world financial workflows, curating evaluation datasets, and validating AI outputs in live client pilots.
This is a hands-on role for someone who already knows finance deeply and wants to shape how AI does that work, rather than advise on it from a distance.
Your financial judgment sets the standard the product is held to, and you should expect to be in the detail day to day, in a fast-moving startup where the playbook is still being written.

Build the evals - design proprietary benchmarks, test suites, and datasets for model evaluation
Partner with ML Research - work with researchers to refine models, shape prompt strategies, and validate outputs against expert standards
As one of Samaya's Finance Product Managers, you'll own the domain strategy that helps investment professionals find actionable insights in vast, noisy datasets.
zoom in on a sector or basket of companies and manage the flood, but lose sight of adjacent dynamics that move markets.
Or zoom out to track broad themes, but lose the needle-in-a-haystack details that drive precise decisions.
Equipment: Create your ideal workspace with an office Equipment allowance to set up what works best for you.

For investors, this means exponentially more depth, breadth, and speed required on every decision.

The cash compensation range for this role is $140,000 - $210,000.
In addition to the base salary, we may consider equity as part of our total compensation package.

Health: Access comprehensive health insurance, including medical, dental, vision, flexible spending account (FSA), and short-term disability.
Wealth: Support for your long-term financial wellbeing with a 401(k) and pre-tax benefits (e.g. commuting).
Rest: Enjoy flexibility to rest and recharge as needed, with unlimited PTO (Paid Time Off).
Institutional Finance Background - 3+ years at a top-tier investment bank, hedge fund, asset manager, or buy-side/sell-side research team (equity research included)
Startup exposure - prior experience at a fast-growing fintech or AI startup

defining real-world financial workflows, curating evaluation datasets, and validating AI outputs in live client pilots.
Your expertise will directly shape the platform's capabilities in valuation, modeling, and due diligence.
We are committed to ensuring an equitable selection process for everyone and welcome applicants from varied backgrounds to enrich our team.
If you require accommodations or adjustments during our recruitment process, please inform us.
Interview Accommodations: We are committed to ensuring an equitable selection process for everyone and welcome applicants from varied backgrounds to enrich our team.

Employer: We do not discriminate on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.
Visa Sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
About Samaya
Samaya builds Expert AI Agents that turn information from the global financial market into investment conviction.

However, we aren't able to successfully sponsor visas for every role and every candidate.
If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We do sponsor visas!

This listing is sourced directly from Samaya AI's careers page and normalized into a canonical job model.