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Physics Informed Neural Networks Jobs in Texas (NOW HIRING)

Senior Data Scientist

Frisco, TX ยท On-site

$128 - $180/hr

Master's degree in Statistics, Econometrics, Mathematics, Operations Research, Physics, Computer ... neural networks, deep learning and its various applications. Continuously following the advancement ...

New

... neural networks. Our work combines deep technical expertise with a strong culture of integrity ... Strong knowledge of CMOS circuit design and semiconductor device physics * Experience with ...

... neural networks. Our work combines deep technical expertise with a strong culture of integrity ... Strong knowledge of CMOS circuit design and semiconductor device physics * Experience with ...

Staff HBM Design Architect

Richardson, TX ยท On-site

$146K - $297K/yr

... neural networks. Our work combines deep technical expertise with a strong culture of integrity ... Strong knowledge of CMOS circuit design and semiconductor device physics * Experience with ...

Staff HBM Design Architect

Richardson, TX ยท On-site

$146K - $297K/yr

... neural networks. Our work combines deep technical expertise with a strong culture of integrity ... Strong knowledge of CMOS circuit design and semiconductor device physics * Experience with ...

Senior Decision Science Analyst - P&C Analytics

Plano, TX ยท On-site

$84K - $111K/yr

Remains informed on current data and analytics trends, (Ex: Cloud, Data Mining, Python, Neural Networks, Sensor data, IoT, Streaming/NRT data) * Identifies opportunities to continue to learn in the ...

Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational ... or Physics. 3+ years of related experience. Certification is required in some areas. Our Senior ...

Showing results 21-40

Physics Informed Neural Networks information

What is a physics informed neural network?

A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.

What are the key skills and qualifications needed to thrive in physics informed neural networks?

To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.

What does a physics informed neural network do?

In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.

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What job categories do people searching Physics Informed Neural Networks jobs in Texas look for? The top searched job categories for Physics Informed Neural Networks jobs in Texas are:
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Infographic showing various Physics Informed Neural Networks job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, and 7% Part Time. Highlights an 100% In-person job distribution.

Senior Data Scientist

Socket.dev

Frisco, TX โ€ข On-site

$128 - $180/hr

Other

Posted 3 days ago

New


Job description

Employee Applicant Privacy Notice

Who we are:

Shape a brighter financial future with us.

Together with our members, weโ€™re changing the way people think about and interact with personal finance.

Weโ€™re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and weโ€™re at the forefront. Weโ€™re proud to come to work every day knowing that what we do has a direct impact on peopleโ€™s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The Role:

The Risk Data Science team is looking for a Senior Data Scientist to develop advanced machine learning and statistical models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas at SoFi. The Data Scientist will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions for underwriting, portfolio management, loss mitigation, and loss forecasting etc. These tasks involve researching and applying state of the art modeling methodologies to solve complex business problems. This role is very rewarding as your work will have a direct and immediate impact on the businessโ€™ profitability.

What Youโ€™ll Do:
  • Develop, implement, and continuously improve machine learning and statistical models that support various credit, risk, and operational procedures including but not limited to underwriting, portfolio management, loss mitigation, and loss forecasting, etc.
  • Present model performance and insights to Credit, Risk, and Business Unit leaders.
  • Proactively identify opportunities to apply advanced modeling approaches to solve complex business problems.
  • Explore and leverage in-house and external data sources to enhance model predictive power.
  • Collaborate with the Model Risk Management team to demonstrate models are developed with high level rigor that satisfy Model Risk Management and Governance requirements.
  • Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking
  • Collaborate with the Product and Engineering teams to improve the model development, deployment, monitoring, and model re-calibration/re-build process.
  • Explore and apply in-house and open-source machine learning and statistical tools and algorithms to develop and improve models.
What Youโ€™ll Need:
  • Masterโ€™s degree in Statistics, Econometrics, Mathematics, Operations Research, Physics, Computer Science, Engineering, or quantitative field required. PhD degree preferred.
  • 3+ years of relevant work experience in building and implementing machine learning and statistical models.
  • Excellent logic reasoning and communication abilities when interpreting business requirements and translating them into effective data solutions.
  • Strong skills in writing efficient SQL queries and Python code to create complex attributes, especially with large datasets.
  • Strong sensitivity to details in data and proactively investigate them to uncover unknown patterns.
  • Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc.
  • Demonstrated sophisticated experience in building efficient and reliable pipelines that interact with large datasets stored in SageMaker and Snowflake, automating recurring processes such as data extraction and processing, feature selection, model training, model monitoring, and generating documentation templates to support reproducibility and cross-functional collaboration.
  • Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but are not limited to) regression, classification, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications. Continuously following the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies
  • Strong programming skills in Python and machine learning libraries (e.g., sklearn, lightgbm, xgboost, pytorch, tensorflow, keras, etc.)
Nice To Have:
  • Experience in a lending organization.
  • Experience with model documentation and delivering effective verbal and written communication.
  • Experience in working closely with Product, Engineering, and Model Risk Management teams.
  • Experience with AWS or GCP.

Compensation and Benefits

The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidateโ€™s experience, skills, and location.

This role may also be eligible for a bonus and/or long term incentives. Your recruiter will provide more information to you. All roles are eligible for competitive benefits. More information about our employee benefits can be found in the link below.

Benefits

To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi & Galileo page!

US-Based Base Compensation

$128,000โ€”$180,000 USD

Compensation and Benefits

The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidateโ€™s experience, skills, and location.

To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!

SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.The Company hires the best qualified candidate for the job, without regard to protected characteristics.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.New York applicants: Notice of Employee RightsSoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.

Internal Employees

If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

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