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Salary: USD 225,000 - 250,000 / annual
YipitData is a unicorn-backed ($1B+ valuation, $475M Series C from Carlyle Group) market research and analytics firm specializing in alternative data for the disruptive economy. The company analyzes billions of data points daily to deliver actionable insights across software, AI, cloud, e-commerce, ridesharing, and payments to top investment funds and Fortune 500 companies.
You will lead YipitData's Systematic Data Products & Feeds business as a strategic business leader, turning a growing portfolio into a major, repeatable growth engine. This is a P&L ownership role reporting to senior leadership, responsible for strategy and performance across quant products, consumer transaction data, consumer receipt data, and the broader data feeds portfolio.
Key responsibilities include:
**Business Performance**: Own ARR growth, retention, profitability, and overall financial performance. Translate strategy into a multi-year business plan with clear targets, assumptions, resource requirements, and risks. Establish business scorecards and provide leadership visibility on performance and trajectory.
**Portfolio & Investment Strategy**: Determine which markets, buyer segments, and systematic workflows to pursue and how to win. Shape transaction data, B2B data, quant products, and other feeds into a coherent portfolio. Identify opportunities to turn existing data into new products and revenue streams. Allocate investment across the portfolio, making explicit decisions about where to scale, maintain, pivot, or exit. Prioritize reusable capabilities and data assets.
**Commercial Engine**: Define a clear portfolio proposition communicating differentiation. Own packaging, pricing, bundling, and entitlements. Partner with Revenue and Client Strategy to build repeatable sales, trial, onboarding, adoption, retention, and service motions for systematic-data buyers. Build relationships with quantitative researchers, data scientists, and portfolio managers. Use client feedback and performance signals to refine strategy.
**Operating Model**: Create an operating cadence connecting business priorities with product roadmaps, data investments, and engineering dependencies. Establish clear decision rights and accountability across business, product, quant, data, engineering, revenue, and operations. Resolve cross-product dependencies. Build the leadership structure and organizational capabilities required to scale.
**Future-Proofing**: Set business requirements for systematic products (point-in-time integrity, history, coverage, stable identities, lineage, joinability, delivery reliability). Shape distribution strategy across feeds, APIs, MCPs, agents, cloud platforms, notebooks, marketplaces, and third-party integrations. Apply AI and automation to accelerate dataset evaluation, QA, documentation, signal testing, support, and implementation. Anticipate changes in systematic and agentic investor workflows.
You will unite leaders across Product, Quant, Data, Engineering, Revenue, Client Strategy, and Operations behind one business plan, determining where the company competes, how it wins, and where it invests.
**Requirements**
Required:
- Senior leadership experience building or scaling a data, fintech, information-services, analytics, or enterprise-software business
- Direct P&L ownership including revenue performance, multi-year planning, resource allocation, and investment tradeoffs
- Proven track record turning individual products or differentiated data assets into a coherent, repeatable commercial business
- Strong market and portfolio judgment with 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
- Ability to build strong client relationships and translate market evidence into clear business and product choices
- Experience leading through matrixed organizations, 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
- Demonstrated ability to build teams, develop leaders, and design scalable organizations
- Exceptional written, verbal, and executive communication skills
Preferred:
- Experience serving quantitative investors, systematic funds, data scientists, or technical investment personas
- Experience in alternative data, market data, financial information services, or investment-research products
- Familiarity with systematic-data requirements (point-in-time integrity, backtesting, identity mapping, schema stability, lineage, 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
