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Freelance Machine Learning Quant Jobs in New York

Unchain Data

Crypto Quant Researcher

Manhattan, NY · On-site

$100 - $150/hr

Our teams of engineers, traders and researchers harness leading-edge quantitative research and the accelerating power of compute, machine learning and AI to power our analytics and tackle the market ...

New

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 ...

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 ...

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 ...

AQR

Data Scientist, Machine Learning

Greenwich, CT · On-site

Partner directly with quantitative researchers to understand the needs of a specific machine learning project and collaboratively produce data that best fits the model and project * Transform raw ...

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Freelance Machine Learning Quant information

What is the difference between Freelance Machine Learning Quant vs Freelance Data Scientist?

AspectFreelance Machine Learning QuantFreelance Data Scientist
CredentialsStrong background in quantitative finance, mathematics, and machine learningBackground in statistics, data analysis, and programming; often less finance-specific
Work EnvironmentFinancial firms, hedge funds, or independent consulting in financeVarious industries including tech, healthcare, marketing, and finance
Industry UsagePrimarily in finance and trading

Freelance Machine Learning Quants focus on applying machine learning techniques to financial markets, often working with trading strategies and risk models. Freelance Data Scientists have a broader scope, working across multiple industries to analyze data, build predictive models, and generate insights. While both roles require strong technical skills, the finance-specific knowledge distinguishes the Freelance Machine Learning Quant from the Freelance Data Scientist.

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Freelance Machine Learning Quant jobs near you

Machine Learning Researcher - PhD: 2027

SIG Susquehanna

Manhattan, NY • On-site

$270 - $330/hr

Other

Posted 16 days ago

Job description

Overview

Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.


We’re looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.


What you\'ll do

  • Research and develop deep learning models to generate and enhance systematic trading signals and strategies across asset classes.

  • Collaborate closely with researchers, traders, and developers to improve alpha generation and identify new algorithmic trading strategies.

  • Design and conduct rigorous experiments using modern machine learning frameworks to improve predictive signals and overall trading performance.

  • Apply scientific methods to extract actionable signals from complex datasets, deepening the understanding of market behavior.

  • Translate research insights into production-ready models that can be implemented, tested, and validated in live trading environments.

  • Partner with engineering and trading teams to deploy, monitor, and iterate on models that drive trading decisions and execution outcomes.


What we\'re looking for

  • PhD in computer science, machine learning, mathematics, physics, statistics, or a related field

  • Strong track record of applying ML in academic or industry settings, with 5+ years of experience building impactful deep learning systems

  • A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR

  • Strong programming skills in Python and/or C++

  • Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments

  • Hands-on experience applying deep learning on time series data

  • Strong foundation in mathematics, statistics, and algorithm design

  • Excellent problem-solving skills with a creative, research-driven mindset

  • Demonstrated ability to work collaboratively in team-oriented environments

  • A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment

  • Visa sponsorship is available for this position


The annual base pay for this role is $300,000. Susquehanna considers factors such as scope and responsibilities of the position, work experience, education/training, key skills, as well as market and organizational considerations when extending an offer.


What we offer

  • Collaborate with a world-class team of researchers, engineers, and traders

  • Gain access to best-in-class financial data and high-performance computing resources

  • Directly impact real-time trading performance through your work

  • Thrive in a collaborative, intellectually rigorous environment with a global footprint


About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.


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