Product Manager, Quant Platform

Remote from
USA flag
USA
Annual salary
Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Employment type
Full Time,
Job posted
Apply before
10 Jul 2026
Experience level
Midweight
Views / Applies
54 / 6

About YipitData

YipitData provides reliable insights to investment funds and corporations by analyzing billions of data points.

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

YipitData is a leading market research firm backed by Carlyle Group, valued over $1B. They seek a Product Manager to own and scale their quant platform, turning alternative data into factor products for systematic investors. The role involves defining the factor library, collaborating with quant researchers and engineers, and conducting customer research. This is a remote-friendly opportunity based in the US, with a focus on mastery, ownership, and transparency. The position sits at the intersection of quant research, data products, engineering, and go-to-market.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight This role requires deep domain expertise in quant finance, data engineering, and product management, as well as the ability to navigate complex stakeholder needs and build a platform from ground up, making it challenging but not extremely rare.

Salary Analysis

Median Highly Competitive
$175,000
US Market
$120k – 200k
0 $220k
AI Insight The offered salary is not specified, but based on the US market, the median for a Product Manager in alternative data/quant platform is approximately $175,000. This is competitive for a senior-level role at a high-growth, well-funded company like YipitData.

Key Skills

Product Management Quant Research Alternative Data Factor Library Signal Research Data Products Python Customer Research Go-to-Market Strategy Pipeline Engineering

Dear Hiring Manager,

I am excited to apply for the Product Manager, Quant Platform role at YipitData. With a background in product management and a strong understanding of alternative data and quantitative finance, I am eager to drive the development of your quant platform and factor library.

In my previous role at a data analytics firm, I led the productization of complex datasets, collaborating with quant researchers and engineering teams to deliver scalable, high-alpha signals. My experience in customer research and go-to-market strategy aligns perfectly with the needs of this role.

I am particularly drawn to YipitData's culture of ownership and transparency. I thrive in fast-paced environments where I can take full ownership of a product vision and work cross-functionally to bring it to market.

I look forward to the opportunity to contribute to YipitData's growth and help shape the future of systematic investing.

Sincerely,
[Your Name]

How would you approach defining the initial factor taxonomy for our quant platform?
I would start by conducting customer research to understand the key factor types (e.g., growth, value, momentum) that systematic investors prioritize. Then, I would collaborate with quant researchers to identify which of our proprietary datasets can generate high-alpha signals for each factor, and sequence the development from a minimal viable taxonomy to a comprehensive one.
Describe a time you had to balance conflicting priorities between engineering, research, and business teams. How did you handle it?
In a previous role, I had to prioritize between building a new data pipeline (valuable for research) and improving existing data delivery stability (critical for clients). I facilitated a cross-functional meeting to align on business impact, then used a weighted scoring framework to decide to first enhance stability for key clients while allocating a small team to prototype the new pipeline.
How do you ensure that factor pipelines are both scalable and accurate when moving from research to production?
I would implement rigorous QA frameworks, including automated data validation, reference data checks, and monitoring for drift. I would also work with engineers to design pipelines that are modular and configurable, so as we add new datasets and factors, the infrastructure can be reused and tested. Additionally, I'd establish clear SLAs and run periodic backtests to verify accuracy.
Can you explain how you would translate a quant researcher's signal idea into a standardized product?
I would first document the signal's methodology, including data inputs, calculation logic, and target universe. Then I would work with the researcher to create a design document covering factor definitions, taxonomy, and update cadence. Next, I'd partner with engineering to build a scalable pipeline that outputs standardized files (e.g., factor exposures, metadata). Finally, I'd oversee beta testing with a few clients to gather feedback and iterate.
What experience do you have with alternative data, and how do you stay current with trends in quantitative finance?
I have worked with transaction data, web scraping, and satellite imagery to generate signals for hedge funds. I stay current by reading research from groups like Two Sigma and AQR, attending quant conferences, and maintaining a network of industry contacts. I also regularly experiment with new datasets and share findings with my team.

About Us:

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 ofInc’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.

About the Role:

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.

In this role, you will:

  • Quant Platform & Factor Library Development
    • 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.
  • Signal-to-Pipeline Engineering Partnership
    • 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
  • Customer Research & End-Market Strategy
    • 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
  • Go-to-Market & Commercial Accountability
    • 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
  • Cross-Functional Collaboration
    • 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

What We’re Looking For:

  • Required
    • 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
  • Preferred
    • 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)

What We Offer:

  • Our compensation package includes competitive salary and comprehensive benefit offerings:
    • 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. See more on our high-impact, high-opportunity work environment above!
    • The annual on-target earnings for this position is anticipated to be up to $180-200k. The final offer may be determined by a number of factors, including, but not limited to, the applicant’s experience, knowledge, skills, abilities, as well as internal team benchmarks. 
    • The compensation package also includes equity.

This role may be performed fully remotely within the United States. Please note that our US headquarters are located in NYC. We also have offices in Austin, Miami, Los Angeles (CA), and Cupertino (CA). If the remote work is performed outside of these offices, income may be subject to New York State tax withholding.

Please note that for this position, we are not able to consider candidates who currently or in the future will require visa sponsorship.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal-opportunity employer.

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