Founding Data Scientist, Pricing & Monetization
Posted bythe hiring team· about 9 hours ago
Posted bythe hiring team· about 9 hours ago
Founding Data Scientist, Pricing & Monetization
USD 340,000 – USD 380,000
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About this role
About the Team
the company Pricing team sits at the center of product, go-to-market, finance, and strategy. We define how the company packages, prices, and scales access to our products across consumer, SMB, and enterprise customers, turning deeply technical product usage and market signal into company-level decisions.
We’re looking for a senior Data Scientist to be the first dedicated data science hire on the Pricing team. This is a rare zero-to-one role with direct exposure to the company CFO, Head of Pricing, and senior leaders across Product and GTM. You will help build the analytical foundation for pricing at the company, shape executive decisions, and define what excellent pricing data science looks like.
About the Role
As a founding Data Scientist for Pricing, you will design the analyses, models, experiments, and decision frameworks that guide pricing strategy across the company business. You’ll work side-by-side with the CFO, Head of Pricing, and senior leaders across Product and GTM on ambiguous, high-leverage questions where simple reporting is not enough, translating customer behavior, product usage, revenue outcomes, and market dynamics into clear recommendations.
This role combines hands-on technical depth with executive-ready storytelling. You should be excited to build from first principles, operate with high independence, and influence decisions that shape how the company grows and serves customers around the world.
In This Role, You Will
Serve as a senior analytical partner to the CFO, Head of Pricing, Product, and GTM leaders on pricing and monetization decisions.
Build the analytical foundation for pricing across consumer, SMB, and enterprise segments, from exploratory analysis to repeatable decision systems.
Design and execute analyses that connect customer behavior, product usage, conversion, retention, revenue outcomes, and pricing strategy.
Develop models, algorithms, experiments, and decision frameworks for complex pricing, packaging, discounting, and willingness-to-pay questions.
Translate technical work into crisp executive recommendations and practical operating guidance for cross-functional teams.
Identify where a dedicated pricing data science function can create repeatable leverage, helping define the roadmap, standards, and future operating model for the team.
You Might Thrive in This Role If You
Have deep experience using casual inference and other statistical techniques to solve pricing, monetization, packaging, or business strategy problems.
Are energized by ambiguous, zero-to-one work with senior leadership visibility and a chance to write the playbook.
Can move fluidly between hands-on analysis, model-building, experimentation, and strategic decision support.
Have built or influenced sophisticated pricing systems in complex, high-scale environments.
Communicate clearly with executive, business, product, and technical leaders, including when the answer is nuanced or uncertain.
Are excited by a founding role where your work can shape company-level strategy and the future of pricing at the company.
Qualifications
Significant experience in data science, analytics, economics, statistics, machine learning, or a related quantitative field.
Strong technical ability in analysis, modeling, experimentation, causal inference, and data-driven decision-making.
Experience working on pricing, monetization, marketplace dynamics, usage-based pricing, dynamic pricing, packaging, or adjacent high-complexity business problems.
Ability to operate independently in ambiguous environments, define analytical direction from scratch, and bring senior stakeholders along through clear tradeoff framing.
Strong written and verbal communication skills, including the ability to influence executive-level audiences and cross-functional operating teams.
Preferred Qualifications
Prior pricing experience across consumer, SMB, enterprise, marketplace, platform, or AI/API businesses.
Experience building novel pricing models, systems, experimentation programs, or decision frameworks.
PhD preferred; a master’s degree or equivalent practical experience can also be a strong fit.
Experience helping establish a new data science function, operating model, technical roadmap, or executive decision cadence.
About the company
the company is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
The Founding Data Scientist, Pricing & Monetization role with the hiring team offers USD 340,000–380,000 per year. Salary information is published as part of every JobRemotely listing so candidates can self-screen before applying.
Yes — the hiring team has marked this Founding Data Scientist, Pricing & Monetization role as open to candidates based in United States. Eligibility requirements are surfaced in the JobPosting structured data on the listing.
The hiring team uses the JobRemotely structured hiring pipeline: candidates apply through the listing, complete a paid test task or screening, and only then proceed to interviews. This skips the resume black hole and respects everyone's time.
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