
201 - 500 employees
💸 Finance
🏢 Enterprise
Finance • Enterprise • Data Analysis
YipitData is a company that specializes in providing accurate, timely insights on over 1,000 companies by analyzing billions of data points every day. They offer detailed research to help investors make smarter decisions and assist companies in increasing market share, sales, and customer base. YipitData delivers alternative data through a range of datasets, including receipt data, card data, web data, and publicly reported earnings. This data is used to track market trends, consumer behavior, and product categories, enabling businesses to gain transparency into performance metrics. Their services cater to investors, companies, and data partners, with a strong focus on accuracy and near real-time data delivery.
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201 - 500 employees
💸 Finance
🏢 Enterprise
Finance • Enterprise • Data Analysis
YipitData is a company that specializes in providing accurate, timely insights on over 1,000 companies by analyzing billions of data points every day. They offer detailed research to help investors make smarter decisions and assist companies in increasing market share, sales, and customer base. YipitData delivers alternative data through a range of datasets, including receipt data, card data, web data, and publicly reported earnings. This data is used to track market trends, consumer behavior, and product categories, enabling businesses to gain transparency into performance metrics. Their services cater to investors, companies, and data partners, with a strong focus on accuracy and near real-time data delivery.
• Define and own the product spec for our factor library - including factor definitions, universe/coverage rules, methodology notes, historical evidence packs, factor exposure files, QA frameworks, and update cadence • Build and scale a standardized factor taxonomy (e.g., growth factors, acceleration/inflection factors, surprise/revision-type factors) across multiple proprietary datasets • Collaborate with our quant research team to perform deep diligence on datasets and publish high-alpha signal research, translating raw research into repeatable, productized factor pipelines • Sequence the factor library from an initial constrained beta toward a complete library with traditional baseline factor models, alt-data factors, and incremental attribution frameworks. • Take quant researcher signal research and collaborate with engineering partners to turn insights into repeatable, scalable factor computation and delivery pipelines • Define product requirements for factor infrastructure - including reference data dependencies, standardized identifiers, automated QA, and monitoring systems • Own the product-side accountability for ensuring factor pipelines are highly stable, accurate, and delivered on a consistent frequency • Conduct deep customer research to understand key systematic end-user needs, feed architecture designs, integration requirements, and backtesting workflows • Translate customer insights into a product build and prioritization pipeline that serves the full spectrum of quant buyers - from large systematic multi-managers running bespoke models to smaller funds consuming pre-packaged signals • Support pricing, packaging, and competitive positioning decisions for quant products in partnership with GTM teams • Partner closely with our revenue and product marketing teams to build GTM plans for signals and bring them to market - including client-ready case studies, evidence packs, and methodology documentation • Share ARR and P&L accountability alongside Product Specialists / Product Enablement partners for the quant products you own • Collaborate with Product Specialists (our product-sales translators) to enable sales motions, support client conversations, and scale enablement across the quant product portfolio • Partner with Engineering on technical approach, scaled infrastructure, delivery architecture, and reliability - you own strategy and direction; engineering owns implementation • Work closely with Quant Researchers, who function as a key internal customer providing research requirements, content, and deliverables for the external quant end market • Coordinate with Feed Operations on day-to-day delivery, incident management, and operational improvements • Partner with the CS team (who own feed retention and renewal) to drive retention, expansion, and client satisfaction
• 8+ years of product management experience, with a strong preference for experience building products for buy-side systematic / quantitative users • Deep familiarity with the quant / systematic investing workflow - including factor construction, backtesting, signal evaluation, and portfolio construction • Experience defining and shipping data-intensive or quantitative products - factor feeds, signal libraries, analytics platforms, or similar • Strong ability to translate between quantitative research and product/engineering requirements - you can read a research paper and turn it into a product spec • Proven ability to work cross-functionally across research, engineering, sales, and marketing in a high-growth environment • Excellent customer research skills - you know how to run discovery with sophisticated quant buyers and synthesize feedback into product decisions • Strong commercial instinct - comfort with ARR accountability, pricing strategy, and competitive positioning.
• We care about your personal life, and we mean it. We offer flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more! • Your growth at YipitData is determined by the impact that you are making, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust. • The compensation package also includes equity.
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