Job description

Role 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. 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. Your expertise will directly shape the platform's capabilities in valuation, modeling, and due diligence. 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. Responsibilities Product & Domain Translate financial workflows — turn investment banking, private equity, buy-side, and sell-side research workflows into product requirements and success metrics Author playbooks — codify best practices for AI-assisted financial analysis Surface insights — bring high-signal findings back to inform roadmap priorities Evaluation & Pilots 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 Run client pilots — co-pilot pilots with leading financial institutions, gather feedback, and iterate fast Work in the detail — grade answers and audit agent execution traces; getting models to do expert financial work involves a lot that looks like associate-level work Experience Required 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) Deep finance expertise — strong command of one or more of financial modeling, valuation, capital markets research, and deal execution Translates ambiguity — proven ability to turn ambiguous problems into clear requirements and measurable outcomes Exceptional communicator — clear written and verbal communication with senior stakeholders Genuine AI fluency — you use AI in your work concretely, not just in passing Preferred Technical fluency — hands-on scripting in Python or SQL for data analysis Both sides of research — exposure to both sell-side and buy-side research models Startup exposure — prior experience at a fast-growing fintech or AI startup Compensation The cash compensation range for this role is $140,000 - $210,000. Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above. In addition to the base salary, we may consider equity as part of our total compensation package. Benefits 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). Flexibility: Work flexibly with a hybrid setup - typically team members spend a minimum of three days in the office per week. Travel: Grow and connect with a travel budget that encourages conference attendance, customer visits, and team gatherings. Equipment: Create your ideal workspace with an office Equipment allowance to set up what works best for you. Inclusive Hiring Interview Accommodations: 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. Equal Opportunity 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 AI builds Expert AI Agents for investment professionals, supporting high-stakes investment workflows across leading financial institutions. By combining finance-specific AI models with deep reasoning over institutional context and global markets, Samaya helps investors go from information to conviction. Samaya is deployed at enterprise scale across hedge funds, asset managers, and banks, including more than 12,000 professionals at one of the world's largest financial institutions. Built by a team from Google DeepMind, Meta, Microsoft, and Stanford with 100+ papers and 50k+ citations, it achieves 98% accuracy on financial reasoning tasks where generic LLMs reach 53%. Backed by leading AI investors including NVIDIA, Databricks Ventures, NEA, Eric Schmidt, and Yann LeCun, Samaya continues to advance the next generation of AI for investment professionals. Our Operating Principles Put Users first. Our users rely on us to do their jobs. We exist because our users trust us to help them achieve their goals. In return for this trust users place in us, we keep their needs as our top priority. Win as a collective. We are high achievers with a drive to succeed. We build strong bonds over this shared drive. We dive in to help when one of us needs it. We’re kind to each other and boost each other to succeed and grow professionally and personally. We build trust with each other by making commitments and consistently delivering on them. This trust means we genuinely support each other, embracing feedback as a tool for growth and improvement. We win by operating this way, as one team. Focus and iterate quickly. Bias for action makes us build and learn quickly. Iterating fast requires clarity on what outcomes we are targeting and why. Prioritizing the important things, taking full ownership and initiative, making fast initial progress, and rapid iterations lead to the best outcomes. Innovate Relentlessly. We pursue novel insights, challenging the status quo and reimagining how things are done. We aren’t attached to the past when improving our product and how we work in the future. We actively invest time in innovation, thinking “outside the box” to consistently raise our standards. Prioritize Outcomes over Egos . We are committed not to a person, an idea, or an opinion but to continuously making progress to our goals. Sometimes, our goals are ambiguous; in those moments, we iterate, learn, and move on to the next inquiry. We ask the tough questions with kindness, dropping our egos in our pursuit of evidence. For our business goals, we learn from our users. For our scientific goals, our understanding is built through rigorous experimentation, research, and observation. For our personal goals, we embrace candid feedback and collaborative learning to guide our progress.

Requirements

Must-haves

Product & Domain
Translate financial workflows — turn investment banking, private equity, buy-side, and sell-side research workflows into product requirements and success metrics
Author playbooks — codify best practices for AI-assisted financial analysis
Surface insights — bring high-signal findings back to inform roadmap priorities
Evaluation & Pilots
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
Run client pilots — co-pilot pilots with leading financial institutions, gather feedback, and iterate fast
Work in the detail — grade answers and audit agent execution traces; getting models to do expert financial work involves a lot that looks like associate-level work
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)
Deep finance expertise — strong command of one or more of financial modeling, valuation, capital markets research, and deal execution
Translates ambiguity — proven ability to turn ambiguous problems into clear requirements and measurable outcomes
Exceptional communicator — clear written and verbal communication with senior stakeholders
Genuine AI fluency — you use AI in your work concretely, not just in passing

Nice-to-haves

Technical fluency — hands-on scripting in Python or SQL for data analysis
Both sides of research — exposure to both sell-side and buy-side research models
Startup exposure — prior experience at a fast-growing fintech or AI startup

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Pto

Paid Time Off