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Physics Informed Machine Learning Jobs in Cumming, GA

... drive informed decision-making. * Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team. What you bring:

Do you enjoy combining software engineering, analytics, machine learning, and Generative AI to ... and making timely and informed decisions to enhance investigations. You can learn more about ...

AI Engineer

Atlanta, GA · On-site

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

... informed decision-making and driving business growth. Within our Technology Consulting practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Sr Data Scientist

Atlanta, GA · On-site

$94.50 - $115.50/hr

Your main objective is to leverage advanced analytics and machine learning techniques to deeply ... physics or engineering. What You'll Get * Up to 40% off the base rate of any standard Hertz Rental

This position offers the opportunity to work with data to drive informed decision-making and ... Knowledge of machine learning techniques and applications. * Familiarity with database management ...

Showing results 21-40

Physics Informed Machine Learning information

See Cumming, GA salary details

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How much do physics informed machine learning jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for physics informed machine learning in Cumming, GA is $17.90, according to ZipRecruiter salary data. Most workers in this role earn between $11.15 and $22.74 per hour, depending on experience, location, and employer.

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 Cumming, GA?

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

What job categories do people searching Physics Informed Machine Learning jobs in Cumming, GA look for?

The top searched job categories for Physics Informed Machine Learning jobs in Cumming, GA are:

What cities near Cumming, GA are hiring for Physics Informed Machine Learning jobs?

Cities near Cumming, GA with the most Physics Informed Machine Learning job openings:

Data Scientist Lead

FIS

Atlanta, GA • On-site

Full-time

Posted 11 days ago


FIS Global rating

7.4

Company rating: 7.4 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

169th of 247 rated software companies


Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role:

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you'll be doing:

  • Lead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
  • Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
  • Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
  • Communicate complex analytical findings through compelling storytelling, executive-ready presentations, dashboards, visualizations and self-service analytics tools. that drive informed decision-making.
  • Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring:

  • Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • 5+ years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
  • Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
  • Hands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
  • Demonstrated experience building and deploying machine learning models in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
  • Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Nice to have:

  • Experience within the Payments, Banking, or Financial Services industry.
  • Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
  • Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
  • Working familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the chance to shape the future of fintech. At FIS, we offer you:

  • A voice in the future of fintech
  • Always-on learning and development
  • Collaborative work environment
  • Opportunities to give back
  • Competitive salary and benefits


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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What FIS Global employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


FIS logo

About FIS

Sourced by ZipRecruiter

FIS is a leader in technology and services that helps businesses and communities thrive by advancing commerce and the financial world. For over 50 years, FIS has continued to drive growth for clients around the world by creating tomorrow’s technology, solutions and services to modernize today’s businesses and customer experiences. By connecting merchants, banks and capital markets, we use our scale, apply our deep expertise and data-driven insights, innovate with purpose to solve for our clients’ future, and deliver experiences that are more simple, seamless and secure to advance the way the world pays, banks and invests. Headquartered in Jacksonville, Florida, FIS employs more than 55,000 people across 50+ countries, dedicated to helping our clients be ahead of what’s next. FIS offers more than 450 solutions and processes over $75b of transactions around the planet. FIS is a Fortune 500® company and is a member of Standard & Poor’s 500® Index.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Jacksonville , FL, US

Year founded

1968

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