Product Manager, Quant Platform

YipitData

3d•$180,000 - $200,000•Remote

About The Position

YipitData is a leading market research and analytics firm for the disruptive economy, recently valued at over $1B. We analyze billions of alternative data points daily to provide insights on ridesharing, e-commerce, payments, and more. Our on-demand insights team uses proprietary technology to license, clean, and analyze data for major investment funds and corporations. Recognized as one of Inc's Best Workplaces for three consecutive years, YipitData is a fast-growing technology company backed by The Carlyle Group and Norwest Venture Partners, with offices globally. We foster a people-centric culture emphasizing mastery, ownership, and transparency. This is a remote-friendly opportunity that can be based in NYC or anywhere in the US. At YipitData, we value ownership and impact. Our Data Feeds & Quant business is a rapidly growing segment, and we are seeking a Product Manager to own and scale the platform for our quant product efforts. This role bridges quant research, data products, engineering, and go-to-market strategies. You will transform proprietary and licensed alternative datasets (transaction, email receipt, B2B spend, etc.) into standardized, client-ready factor and signal products for systematic investors. This is a strategic role focused on defining the product vision for our quant platform, establishing its operating model, and launching a new class of products. The Feeds & Quant organization comprises product managers, quant researchers, product specialists, feed operations, and product marketers. We collaborate closely with engineering partners (responsible for technical architecture, infrastructure, and implementation) and with Sales, CS, and Product Specialists. Our clients include sophisticated funds seeking flexible building blocks and smaller managers needing more packaged 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.
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.

Responsibilities

Define and own the product specification 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 across multiple proprietary datasets.
Collaborate with the 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.
Support pricing, packaging, and competitive positioning decisions for quant products in partnership with GTM teams.
Partner closely with 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 owned.
Collaborate with Product Specialists 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.
Work closely with Quant Researchers, who function as a key internal customer providing research requirements, content, and deliverables.
Coordinate with Feed Operations on day-to-day delivery, incident management, and operational improvements.
Partner with the CS team to drive retention, expansion, and client satisfaction.