Head of Data Feeds

Overview

Lead YipitData's Systematic Data Products & Feeds business, owning its strategy, ARR growth, portfolio investment, packaging and pricing, and go-to-market performance.

What you'll do

• Own ARR growth, retention, profitability, and overall financial performance.
• Translate the strategy into a multi-year business plan with clear targets, assumptions, resource requirements, and risks.
• Establish the business scorecard and give the Public Investor Leadership Team a clear view of performance, trajectory, and required decisions.
• Determine which markets, buyer segments, and systematic workflows YipitData will pursue and how it will win.
• Shape transaction data, B2B data, Quant products, and other feeds into a coherent portfolio rather than a collection of independent offerings.
• Identify opportunities to turn existing data into new products, use cases, and revenue streams.
• Allocate investment across the portfolio, making explicit decisions about where to scale, maintain, change course, or stop.
• Prioritize capabilities and data assets that can be reused across multiple products, workflows, and markets.
• Define a clear portfolio proposition that communicates how YipitData's Systematic Data products fit together and why they are differentiated.
• Own packaging, pricing, bundling, entitlements, and other core business-model decisions.
• Partner with Revenue and Client Strategy to build repeatable sales, trial, onboarding, adoption, retention, and service motions for systematic-data buyers.
• Build strong relationships with quantitative researchers, data scientists, portfolio managers, and other sophisticated data buyers.
• Use client feedback, product usage, pipeline performance, and retention signals to continually refine the commercial strategy.
• Create an operating cadence that connects business priorities with product roadmaps, data investments, engineering dependencies, and commercial execution.
• Establish clear decision rights and accountability across business, Product, Quant, Data, Engineering, Revenue, and Operations.
• Resolve cross-product dependencies and sequencing conflicts so the portfolio operates as one business.
• Build the leadership structure, talent, and organizational capabilities required to scale.
• Set the business requirements that make systematic products trusted and usable, including point-in-time integrity, history, coverage, stable identities, lineage, joinability, and delivery reliability.
• Shape the portfolio's distribution strategy across feeds, APIs, MCPs, agents, cloud platforms, notebooks, marketplaces, and third-party integrations.
• Apply AI and automation to accelerate dataset evaluation, quality assurance, documentation, signal testing, support, and client implementation.
• Anticipate changes in systematic and agentic investor workflows and translate them into new business and product opportunities.

What you'll need

• Senior leadership experience building or scaling a data, financial-technology, information-services, analytics, or enterprise-software business.
• Direct ownership of a P&L or business line, including revenue performance, multi-year planning, resource allocation, and investment tradeoffs.
• A record of turning individual products or differentiated data assets into a coherent, repeatable commercial business.
• Strong market and portfolio judgment, with the ability to choose among competing buyer segments, growth opportunities, and investments.
• Experience developing pricing, packaging, go-to-market, onboarding, and service models for sophisticated enterprise or technical customers.
• The ability to build strong client relationships and translate market evidence into clear business and product choices.
• Experience leading through a matrixed organization, establishing decision rights, aligning functional leaders, and creating execution discipline.
• Sufficient technical fluency to engage credibly on data quality, methodologies, schemas, APIs, infrastructure, and delivery reliability.
• A demonstrated ability to build teams, develop leaders, and design organizations that can scale.
• Exceptional written, verbal, and executive communication skills, with the ability to turn complexity into clear direction and decisions.

Nice to have

• Experience serving quantitative investors, systematic funds, data scientists, or other technical investment personas.
• Experience in alternative data, market data, financial information services, or investment-research products.
• Familiarity with systematic-data requirements such as point-in-time integrity, backtesting, identity mapping, schema stability, lineage, and reproducibility.
• Experience commercializing data through feeds, APIs, cloud platforms, MCPs, marketplaces, third-party integrations, or agentic interfaces.
• Experience evaluating, sourcing, licensing, or managing third-party data partnerships.
• Experience using AI and automation to improve data-product development, quality, evaluation, or client delivery.

Details

• Fully remote within the United States; the US headquarters is in NYC, and income may be subject to New York State tax withholding.
• Annual base salary range of $225k-$250k, plus eligibility for an annual performance-based bonus of up to 25% and equity.
• Flexible work hours and flexible vacation.