Curate, cleanse, validate, and maintain large US equity and options datasets; integrate fundamental and alternative data; build data pipelines for research and trading; perform statistical and ML analysis to identify market patterns; document data provenance and collaborate with engineers and traders to deploy production-grade models.
We are seeking a highly analytical and detail-oriented Quantitative Researcher to join our dynamic research team. The ideal candidate will have deep experience curating and analyzing a broad range of trading-related data sources-including traditional market data, fundamental datasets, and other vendor-supplied information. This role will contribute to the development of innovative trading strategies, support data-driven decision-making, and collaborate closely with trading, technology, and data acquisition teams.
Your Core Responsibilities:
Your Skills and Experience:
#LI-DNP
Your Core Responsibilities:
- Curate, cleanse, and validate large volumes of market data, focusing on US equity and equity options
- Integrate, preprocess, and evaluate fundamental & alternative data sources
- Work closely with data acquisition & global data team to assess data quality
- Build and maintain robust data pipelines for research and live trading environments
- Perform data analysis ad statistical modeling to identify patterns and inefficiencies in the market
- Ensure the accuracy, completeness, and timeliness of datasets used in quantitative modeling.
- Document research processes, data provenance, and results with high standards of clarity and reproducibility
- Collaborate with software engineers and traders to translate research into production-grade models and tools
- Conduct quantitative research and analysis to support and enhance trading strategies
Your Skills and Experience:
- 3+ years of experience in a quantitative research or data-focused role in financial markets, ideally in a systematic trading environment
- Proven experience working with a diverse range of trading and financial data
- Must have previous knowledge of options markets and experience working with options data
- Hands-on experience integrating and analyzing non-market data sources is a plus
- Strong understanding of data vendor landscape
- Advanced proficiency in Python
- Experience with databases (SQL) and handling large datasets efficiently
- Familiarity with real-time data systems and tick-level data processing
- Familiarity with statistical and machine learning techniques
- Exceptional attention to detail and a systematic approach to problem-solving
- Strong written and verbal communication skills
#LI-DNP
IMC Trading New York, New York, USA Office
IMC Trading New York City Office
New York, New York, United States, 10017
Similar Jobs at IMC Trading
Fintech • Machine Learning • Software • Financial Services
Supports global recruiting operations by improving processes, managing cross-functional projects, and enabling recruiters and coordinators. Evaluates AI and automation opportunities, pilots recruiting technology, partners with HRIS on ATS systems, creates documentation and training, and translates stakeholder feedback into operational improvements. Requires frequent travel to other offices and focuses on efficient, consistent recruiting outcomes across regions.
Top Skills:
Applicant Tracking SystemsArtificial IntelligenceAutomationGreenhouseHris
Fintech • Machine Learning • Software • Financial Services
Conduct quantitative research for proprietary trading strategies by analyzing high-frequency market data, developing statistical and machine-learning models, building simulations and backtesting tools, and evaluating model performance. Collaborate with traders and developers to validate algorithms, improve pricing and execution, assess production readiness, prioritize research initiatives, and integrate validated models into low-latency trading systems. Mentor graduate researchers and interns.
Top Skills:
Algorithm DesignBacktestingDaskDerivatives PricingFinancial MathematicsHigh-Frequency TradingLightgbmLow-Latency Trading SystemsMachine LearningMarket MicrostructureMatplotlibNumbaNumerical OptimizationNumpyOptimizationPandasPolarsPortfolio ManagementPythonPyTorchRegression AnalysisRisk ModelingScikit-LearnScipySimulationStatistical InferenceStatistical LearningStatsmodelsTime-Series AnalysisXgboost
Fintech • Machine Learning • Software • Financial Services
Operate and improve global developer platform infrastructure supporting source control, CI/CD, artifact repositories, build systems, observability, and AI services. Responsibilities include reliability and performance optimization, high availability, disaster recovery, incident response, capacity planning, automation, on-call practices, cloud SaaS integration, and collaboration with global development teams. The role requires hands-on Linux, programming, Kubernetes, Docker, CI/CD, security, and infrastructure operations experience.
Top Skills:
AWSBazelDockerGitlabGitlab CiGoJenkinsKubernetesLinuxLitellmNexusPythonShell ScriptingTeamcityUnix
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

.png)