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Machine Learning Finance Jobs in Connecticut (NOW HIRING)

AI/ML Development Analyst

Norwalk, CT · On-site

$100K - $150K/yr

Design, develop, and deploy machine learning and AI-driven solutions for business and financial applications. * Build and implement Agentic AI systems , including autonomous workflows and multi-agent ...

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ...

Provide technical leadership across machine learning, statistical modeling, feature engineering ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

Data Scientist

Meriden, CT · On-site

$60 - $64/hr

The ideal candidate will have a strong background in data analysis, machine learning, and ... Provide sensitive financial information such as credit card numbers or banking information.

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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 Jul 13, 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 job makes $1,000,000 a year?

In the field of machine learning finance, highly senior roles such as Chief Data Officer or Quantitative Hedge Fund Manager can earn $1,000,000 or more annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, extensive experience, and expertise in algorithms, financial modeling, and programming tools like Python or R.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence or machine learning within finance or technology sectors, often involving advanced skills in data analysis, programming, and model development. Such roles may include AI research scientists, machine learning engineers, or senior data scientists, and usually require extensive experience, specialized certifications, and proficiency with tools like Python, TensorFlow, or cloud platforms.

Can machine learning be used in finance?

Machine learning is widely used in finance for tasks such as risk assessment, fraud detection, algorithmic trading, and portfolio management. Machine learning finance professionals develop models using programming languages like Python and tools such as TensorFlow or scikit-learn to analyze large datasets and improve decision-making processes.

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 is the salary of ML in finance?

Machine Learning professionals in finance typically earn between $80,000 and $150,000 annually, depending on experience, location, and specific role. Senior roles or those with advanced skills in data analysis, programming, and financial modeling can earn higher salaries, often exceeding $200,000 with bonuses and incentives.

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.

AI Machine Learning Engineer

AI Machine Learning Engineer

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site, Remote

$100K - $151K/yr

Full-time

Re-posted 2 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 110 frontline employees who took The Breakroom Quiz

53rd of 281 rated insurance


Job description

Data Engineer - GE08AE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team.
The Hartford is developing industry-leading AI and machine learning capabilities to improve the various facets of the Global Specialty underwriting experience. On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to accelerate the processes that our partners touch day to day and advance the speed and intelligence with which we make our decisions. As a Machine Learning AI Engineer, you will play a key role in contributing to the designing, building, and operationalizing production-grade AI solutions-partnering closely with product, engineering, and platform leaders to deliver measurable impact.
Our core values
• We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.
• We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.
• We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.
• We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.
• We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.
Responsibilities
• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
• Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
• Accountable for deployment design, development and maintenance of both traditional ML and AI models.
• Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams
• Delivery of critical milestones for model deployment in the AWS and GCP cloud environments.
• Adopt and promote MLOps best practices to the Data Science community.
Minimum Requirements
• Must be authorized to work in the U.S. now and in the future.
• 1+ years of equivalent experience in a research or DevOps function.
• Development experience developing solutions within AWS, GCP or both.
• Exposure to developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
• Familiarity with building and deploying API services within the Cloud.
• Familiarity building CICD pipelines using Jenkins or equivalent
• Exposure with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents
• Experience in Unix, git, and strong object oriented development experience using Python
• Exposure to with workflow automation platforms (Apache Airflow, Autosys, similar)
• Basic understanding of Data Science model development life cycle
• Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).
Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$100,960 - $151,440
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It's Like to Work Here | Perks & Benefits

What The Hartford employees say

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Hartford logo

About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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