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Physics Informed Machine Learning Jobs in Connecticut

Pwc

CTIO AI Engineering Manager

Hartford, CT · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Citadel

$4.5K - $5.8K/wk

Bachelor's or master's degree in mathematics, statistics, physics, computer science, or another highly quantitative field * Strong knowledge of probability and statistics (e.g., machine learning ...

Pwc

US Tech - AI Engineering Senior Associate

Hartford, CT · On-site

$55K - $187K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

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Physics Informed Machine Learning information

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Connecticut?

For Physics Informed Machine Learning jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Connecticut look for?

The top searched job categories for Physics Informed Machine Learning jobs in Connecticut are:

What cities in Connecticut are hiring for Physics Informed Machine Learning jobs?

Cities in Connecticut with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Connecticut as of August 2026, with employment types broken down into 6% Internship, 41% Full Time, 44% Part Time, and 9% Contract. Highlights an 100% In-person job distribution.

Actuarial and Data Science Model Validation

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site

Full-time

Re-posted 2 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 121 frontline employees who took The Breakroom Quiz

57th of 310 rated insurance

Job description

Sr Analyst Model Risk Management - KM07AE
Analyst Model Risk Management - KM08AE
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.
Actuarial and Data Science Model Validation
The Hartford's Model Risk Management function seeks a Risk Manager to join a talented and high-performing Model Risk Management team. The successful candidate will lead efforts to ensure the integrity, accuracy, and compliance of AI and Generative AI (GenAI) models used across the enterprise. The Risk Manager/Validator will independently review, challenge, and validate models to ensure they meet internal model risk management standards, regulatory expectations, and ethical AI principles.
The Hartford utilizes advanced analytics, predictive, AI/ML, and Generative AI models as well as traditional actuarial models in a variety of important and critical business functions. The Model Risk Management team manages model risk across The Hartford by validating these models, implementing consistent policies and standards, and maintaining appropriate model oversight. As part of the team, this role will focus primarily on validating AI and GenAI models across The Hartford and reporting results to key internal stakeholders. Additional responsibilities include educating modeling best practices and spreading model risk awareness across the enterprise.
Responsibilities:
Perform model validations models on AI and GenAI model use cases across The Hartford's functional areas and lines of business to ensure models are performing effectively and efficiently
  • Ensure model calculations, machine learning algorithms, and GenAI methods are accurate and appropriate for intended use
  • Design and build challenger solutions and/or testing methods for tasks such as summarization, question answering, search, data synthesis, llm-as-a-judge etc.
  • Review and assess the quantitative and qualitative testing techniques to ensure model accuracy, robustness, and reliability
  • Assess key data inputs, assumptions, prompt engineering, context engineering for accuracy and appropriateness
  • Review model outputs for accuracy and appropriate downstream usage
  • Deliver effective challenge to key modeling elements such as inputs, calculations, outputs, conceptual soundness, monitoring & controls, documentation, etc.
  • Identify findings and recommendations, including impact analysis, to mitigate model risk and compile clear and concise model validation reports
  • Perform governance accountabilities related to findings tracking, remediation testing, and validation
  • Assist in enhancing existing GenAI model validation framework to include standardization evaluation metrics for performance and reliability, deployment of model validation tools for increased efficiency, and ensure continued alignment with regulatory standards
  • Strengthen partnerships with Data Science teams to keep model risk practices aligned with the proliferation and sophistication of modeling, promote proactive risk management, and share best practices.
  • Pro-actively stay informed with advancements in AI/ML, GenAI, and regulatory expectations for emerging technologies and of department initiatives, deliverables, and reporting
  • Assist with the understanding and testing of cutting-edge tools, such as VertexAI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs, etc.
  • Assist in improving The Hartford's Model Risk Management function in relation to AI and GenAI, by monitoring external environment, implementing emerging best practices, recommending process improvements, and evolving standards/guidelines.

Qualifications:
  • Advanced degree (M.S. or Ph.D.) in a relevant field e.g. Artificial Intelligence, Machine Learning, Computational Science, Engineering, Statistics, Applied Mathematics, Actuarial Science, Computer Science, Quantitative Economics.
  • 3+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI.
  • P&C, Group, Life or related insurance product experience is a plus
  • Strong programming experience across languages/technology platforms including Python, R, SAS/SQL
  • Solid understanding of GenAI concepts including prompt and context engineering, retrieval-augmented generation (RAG), agent workflow, LLM evaluation, familiarity with neural networks
  • Experience in GenAI tools such as Vertex AI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs.
  • Ability to act independently with proactive self-directed accountability and demonstrated experience and consistency in meeting deadlines while adapting to shifting priorities
  • Strong analytical, critical and investigative thinking skills
  • Demonstrated commitment to lifelong learning with a strong desire for continuous development to keep pace with evolving modeling techniques and AI technologies.
  • Solution oriented creativity, innovative thinking, and challenging the status quo.
  • Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.

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:
$108,000 - $162,000
The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience.
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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Hours and flexibility

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Get the full story on Breakroom

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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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