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Machine Learning Finance Jobs in Connecticut (NOW HIRING)

Work with clients to design, develop, and deploy new architectures to support machine learning ... Work alongside clients every step of the way, helping them navigate new challenges, avoid financial ...

Knowledge of Credit Card/Consumer Finance products and business model. * Experience with Machine Learning / AI methodologies and related applications, including generative AI model validation and ...

Entry-Level Machinist

Wallingford, CT

$16.25 - $19.75/hr

... Learning machine operation and capabilities of multiple machines o Running multiple pieces of ... As a growth company with a solid financial position, we are committed to training, promoting from ...

Entry-Level Machinist

Wallingford, CT · On-site

$16.25 - $19.75/hr

... Learning machine operation and capabilities of multiple machines o Running multiple pieces of ... As a growth company with a solid financial position, we are committed to training, promoting from ...

You will be part of a team that helps clients rethink their Finance functions as they leverage new Cloud technology including RPA, Machine Learning and Analytics in conjunction with their ERP ...

You will be part of a team that helps clients rethink their Finance functions as they leverage new Cloud technology including RPA, Machine Learning and Analytics in conjunction with their ERP ...

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Showing results 1-20

Machine Learning Finance information

See Connecticut salary details

$23.8K

$88.1K

$128.9K

How much do machine learning finance jobs pay per year?

As of Jun 17, 2026, the average yearly pay for machine learning finance in Connecticut is $88,119.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,300.00 and $103,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Finance position, and why are they important?

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What are some typical challenges faced by professionals in Machine Learning Finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a Machine Learning Finance job?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

What are popular job titles related to Machine Learning Finance jobs in Connecticut? For Machine Learning Finance jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Machine Learning Finance jobs in Connecticut look for? The top searched job categories for Machine Learning Finance jobs in Connecticut are:

Global Stock Selection Research - Analyst/Associate

AQR

Greenwich, CT

$165K - $200K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago


Job description

About AQR Capital Management

 AQR is a global investment firm built at the intersection of financial theory and practical application. We strive to deliver concrete, long-term results by looking past market noise to identify and isolate the factors that matter most, and by developing ideas that stand up to rigorous testing. By putting theory into practice, we have become a leader in alternative strategies and an innovator in traditional portfolio management since 1998.

At AQR, our employees share a common spirit of academic excellence, intellectual honesty and an unwavering commitment to seeking the truth. We're determined to know what makes financial markets tick - and we'll ask every question and challenge every assumption. We recognize and respect the power of collaboration, and believe transparency and openness to new ideas leads to innovation.

About The Team

The Global Stock Selection (GSS) group is responsible for the portfolio management and research of AQR's strategies relating to individual equities and equity related securities across all global liquid markets. GSS models are applied to market-neutral long/short portfolios in AQR hedge funds as well as to long-only, relaxed-constraint and low volatility portfolios for institutional equity mandates and mutual funds.

Your Role

AQR Capital Management is seeking a talented Researcher to join our team of professionals and focus on our proprietary strategies related to global stock selection. Candidates should be motivated and enthusiastic about implementing new ideas and are expected to be hands-on and self-sufficient in conducting all aspects of research projects. Researchers manage all aspects of the research process including data ingestion and processing, analysis, methodology selection, implementation, testing and performance evaluation. The role will involve collaboration with other researchers, portfolio managers, risk managers and traders to develop new and improve current investment strategies. Your responsibilities may include, but are not limited to:

  • Engage in alpha research and other quantitative analysis to improve current investment strategies in collaboration with existing research team
  • Perform statistical and economic research using traditional financial and alternative data to develop new alpha signals. Successful researchers manage, in collaboration with supervising portfolio manager, all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation.
  • Engage in building, training and fine-tuning machine learning architectures for cross-sectional or time-series Learn how to use the appropriate model for the problem at hand. Construct economically nuanced features from raw data and adjust or develop new frameworks to evaluate their effectiveness. Engage with most recent academic and practitioner literature in the field.
  • Occasionally, conduct research on various aspects of the implementation of investment strategies such as trading cost models, risk models, optimization, and portfolio construction
  • Add features to proprietary research system to implement new research ideas
What You'll Bring
  • B.S. degree from a top institution in computer science, engineering, mathematics, statistics, operations research, physics or another quantitative discipline. Academic or practitioner experience in machine learning methodologies preferred
  • 2-5 years' experience working in a data driven research environment with an alpha focus
  • Experience in quantitative research at a top asset manager or hedge fund preferred
  • Proficient programming in Python required
  • Experience with translating mathematical models and algorithms into code
  • Ability to manipulate large financial data sets for empirical research and handle complex
  • Experience with machine learning software libraries such as scikit-learn, TensorFlow or PyTorch
  • Experience with natural language processing technology, including LLMs and prompt engineering is a plus
  • Strong quantitative skills with demonstrated understanding of mathematics, probability, statistics and linear algebra
  • Nuanced understanding of economic and financial concepts and demonstrated intuition around applying these concepts in a quantitative environment
  • Ability to work independently as well as part of a team
  • Demonstrated ability to express and articulate ideas and thought processes in both verbal and written form

AQR is an Equal Opportunity Employer. EEO/VET/DISABILITY

The salary range for this role is expected to be $165,000 to $200,000.  This is the range that we in good faith believe is accurate for this role at the time of this posting.  We may ultimately pay more or less than the posted range, depending upon factors such as skills, experience, location, or other business and organizational needs.  This wage range may also be modified in the future.

This job is also eligible for an annual discretionary bonus.

We offer comprehensive package of benefits including paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.