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Overnight Machine Learning Quant Jobs in New York

Nvidia

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience). * 8+ years experience applying Machine Learning to operational systems.

Man Group

Principal Quant

New York, NY · On-site

Experience with Machine Learning techniques is a plus * PhD or exceptional Masters / Bachelors ... quantitative subject * Expertise in Python and Linux environments * Comfortable proficiency in C ...

RunSybil

Machine Learning Engineer

New York, NY · On-site

MS or PhD in a quantitative discipline is nice but certainly not required - strong bias for ... Understanding of both modern and classic machine learning techniques * Equally comfortable with ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

A postgraduate degree in Machine Learning, Mathematics, Computer Science, or a related quantitative field * 5 + years experience in Python * 3+ years experience in machine learning research, with a ...

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All JobsMachine Learning Quant JobsOvernight Machine Learning Quant JobsOvernight Machine Learning Quant Jobs in New York

Overnight Machine Learning Quant information

What is the difference between Overnight Machine Learning Quant vs Quantitative Researcher?

AspectOvernight Machine Learning QuantQuantitative Researcher
CredentialsAdvanced degrees in CS, Math, or Stats; programming skillsSimilar; advanced degrees often required
Work EnvironmentFinancial firms, hedge funds, trading desks; fast-paced, data-drivenFinancial institutions, research labs; analytical, research-focused
Industry UsageHigh-frequency trading, algorithmic strategiesMarket analysis, model development
Work HoursOvernight shifts aligned with trading hoursStandard business hours, flexible in some cases

While both roles involve quantitative analysis and programming, Overnight Machine Learning Quants focus on developing models for overnight trading strategies, often working overnight shifts. Quantitative Researchers typically conduct broader market research and model development during regular hours. The roles overlap in skills but differ mainly in work hours and specific application areas.

What are the most commonly searched types of Machine Learning Quant jobs in New York?

The most popular types of Machine Learning Quant jobs in New York are:

What cities in New York are hiring for Overnight Machine Learning Quant jobs?

Cities in New York with the most Overnight Machine Learning Quant job openings:

Overnight Machine Learning Quant jobs near you

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Stamford, CT

Full-time

Posted 23 days ago

Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply