Product Manager, Quant Platform

YipitData

13h•Hybrid

About The Position

YipitData is the leading market research and analytics firm for the disruptive economy and recently raised up to $475M from The Carlyle Group at a valuation over $1B. We analyze billions of alternative data points every day to provide accurate, detailed insights on ridesharing, e-commerce marketplaces, payments and more. Our on-demand insights team uses proprietary technology to identify, license, clean and analyze the data many of the world’s largest investment funds and corporations depend on. For three years and counting, we have been recognized as one of Inc’s Best Workplaces. We are a fast-growing technology company backed by The Carlyle Group and Norwest Venture Partners. Our offices are located in NYC, Austin, Miami, Denver, Mountain View, Seattle, Hong Kong, Shanghai, Beijing, Guangzhou, and Singapore. We cultivate a people-centric culture focused on mastery, ownership, and transparency. This is a remote-friendly opportunity that can sit in NYC (where our headquarters are located) or anywhere in the US, including in any of our US offices listed above. At YipitData, we value ownership and impact. Our Data Feeds & Quant business is one of the fastest-growing segments of YipitData. To accelerate that growth, we’re looking for a Product Manager to own and scale the platform on which our quant product efforts are built. This role sits at the intersection of quant research, data products, engineering, and go-to-market. You will help turn proprietary and exclusively licensed alternative datasets - including transaction data, email receipt data, B2B spend data, and more - into standardized, client-ready factor and signal products for systematic investors. This is not a maintenance role. You will help define the product shape of our quant platform, build the operating model around it, and bring a new class of products to market. Our Feeds & Quant organization includes product managers, quant researchers, product specialists, feed operations, and product marketers. We collaborate closely with engineering partners, who own technical architecture, infrastructure, and implementation, as well as with Sales, CS, and Product Specialists. Together, we serve a wide range of systematic users - from sophisticated funds that want flexible building blocks to smaller managers that need more packaged, immediately usable products.

Requirements

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

Nice To Haves

Experience at a quantitative hedge fund, systematic asset manager, or alternative data provider serving the quant buy-side
Familiarity with alternative data (transaction data, web traffic, app data, email receipts, B2B spend, etc.) and how it's used in systematic strategies
Understanding of factor model frameworks (e.g., Barra, Axioma, or proprietary risk models) and how alpha signals are evaluated relative to traditional factors
Experience building or managing data delivery infrastructure - APIs, flat file feeds, cloud delivery, or data platforms
Comfort with Python, SQL, or similar tools for data exploration (you don't need to be a quant, but you should be able to dig into data)

Responsibilities

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