Quant Research Engineer, Derived Data Products jobs in United States
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Polygon.io · 2 days ago

Quant Research Engineer, Derived Data Products

positionUnited States
timeFull-time
remoteHybrid
seniorityMid Level

Polygon.io is seeking a Quant Research Engineer to design and prototype the next generation of derived market data products. The role involves working with raw market data to create statistically robust datasets used by trading and analytics teams, focusing on methodology and algorithm design.

Developer APIsFinancial ExchangesFinTechStock Exchanges

Responsibilities

Identify high-value derived datasets by understanding how quants, researchers, and data scientists use market data in their workflows
Design and specify quantitative methodologies for new datasets—from statistical assumptions to signal construction to edge-case handling
Prototype algorithms using Python or SQL to validate correctness and performance on large datasets
Build and document rigorous methodology definitions that customers trust and internal teams can implement
Develop robust approaches for data cleaning, normalization, smoothing, interpolation, and event alignment
Work directly with raw market microstructure data (trades/quotes/order books) to derive stable, actionable metrics
Conduct backtests, stress tests, and statistical validation to ensure each dataset behaves as intended

Qualification

Quantitative backgroundMarket data understandingStatistical transformationsPython programmingSQL proficiencyData cleaning techniquesAlgorithm designExperience in quantitative researchProduction engineering conceptsCommunication skills

Required

Strong quantitative background (math, statistics, physics, CS, engineering, or related field)
Deep understanding of market data structure and microstructure: trades, quotes, NBBO, order book dynamics, price formation, volatility, liquidity
Fluency in designing statistical and algorithmic transformations of time-series data
Ability to break down noisy real-world data and rebuild reliable, stable, well-defined derived metrics
Comfort writing Python, SQL, and simple scripts for prototyping and testing (AI can assist; your domain judgment is what matters)
Ability to clearly articulate assumptions, methodology, and edge-case behavior in writing

Preferred

Experience in quantitative research or dataset creation at a market data provider, asset manager, hedge fund, or trading firm is a plus
Familiarity with smoothing filters, microstructure noise models, interpolation schemes, Bayesian methods, or factor construction is a plus
Experience working with large-scale tick data or historical market datasets is a plus
Exposure to production engineering concepts (PRs, CI, code review), though deep engineering expertise is not required

Company

Polygon.io

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Massive empowers participation in the financial markets by providing fair access to market data through a developer-focused platform.
dateFounded in 2016
location
Atlanta, Georgia, USA
people-size51-200 employees
web-link
https://massive.com

Funding

Current Stage
Growth Stage
Total Funding
$6.35M
Key Investors
Headline
2020-09-16Series A· $5.75M
2019-10-02Convertible Note· $0.1M
2019-08-12Convertible Note· $0.5M

Leadership Team

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Quinton Pike
Founder
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Recent News

Newsfile
Massive Closes the Market
2025-11-15
Benzinga.com
EXCLUSIVE: Brokerages Using AI To Help Customers - 'At The Forefront Of Where We're Heading'
2025-11-12
EIN Presswire
Polygon.io is now Massive
2025-11-03
Company data provided by crunchbase