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Scientific Machine Learning Jobs in Utah (NOW HIRING)

Employ Artificial Intelligence and Machine Learning techniques across all business channels ... Scientist. Proficiencies must include a minimum of: experience with Power BI; experience with ...

Employ Artificial Intelligence and Machine Learning techniques across all business channels ... Scientist. Proficiencies must include a minimum of: experience with Power BI; experience with ...

The data scientist role involves solving data-driven Healthcare problems using various machine learning and predictive modeling methods. This person will primarily work as part of the larger Data ...

The data scientist role involves solving data-driven Healthcare problems using various machine learning and predictive modeling methods. This person will primarily work as part of the larger Data ...

The role will focus on extending machine learning, predictive modeling, and analytic components to provide up-to-date intelligence to Healthcare providers maximizing outcomes. An ideal candidate for ...

The data scientist role involves solving data-driven Healthcare problems using various machine learning and predictive modeling methods. This person will primarily work as part of the larger Data ...

The role will focus on extending machine learning, predictive modeling, and analytic components to provide up-to-date intelligence to Healthcare providers maximizing outcomes. An ideal candidate for ...

The data scientist role involves solving technical, data-driven Healthcare problems using computer ... The role will focus on extending machine learning, predictive modeling, and analytic components to ...

The data scientist role involves solving technical, data-driven Healthcare problems using computer ... The role will focus on extending machine learning, predictive modeling, and analytic components to ...

The data scientist role involves solving technical, data-driven Healthcare problems using computer ... The role will focus on extending machine learning, predictive modeling, and analytic components to ...

The data scientist role involves solving technical, data-driven Healthcare problems using computer ... The role will focus on extending machine learning, predictive modeling, and analytic components to ...

... building large-scale machine learning, predictive modeling, and advanced analytics tools ... Qualifications : Required : • Undergraduate degree in Data Science, Statistics, Mathematics ...

Senior Data Scientist

Lehi, UT · On-site

$107K - $183K/yr

As a Senior Data Scientist, you will collaborate with cross-functional stakeholders to identify ... Proficient creating machine learning, predictive modeling, and advanced analytics tools tailored to ...

Data Scientist

Lehi, UT

$120K - $145K/yr

This role focuses on applying machine learning and predictive modeling techniques to improve operational performance and decision-making. You will be part of a broader data science function ...

As a Senior Data Scientist, you will collaborate with cross-functional stakeholders to identify ... Proficient creating machine learning, predictive modeling, and advanced analytics tools tailored to ...

These four domains apply to all aspects of building production data science, machine learning, and AI pipelines in Domo-including use case discovery, ROI estimation and tracking, data ingestion, data ...

These four domains apply to all aspects of building production data science, machine learning, and AI pipelines in Domo-including use case discovery, ROI estimation and tracking, data ingestion, data ...

As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on ... Develop and train machine learning models to solve problems such as prediction, classification, and ...

Sr. Data Scientist

Lehi, UT · On-site

$150K - $185K/yr

Develop and evaluate innovative applications of machine learning within healthcare use cases ... Advanced degree (MS or higher) in Computer Science, Statistics, Mathematics, or a related ...

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Utah? For Scientific Machine Learning jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Scientific Machine Learning jobs? Cities in Utah with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Utah as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Other

Posted 19 days ago


Job description

Swire Pacific Holdings, Inc. DBA Swire Coca-Cola, USA seeks a Data Scientist to conduct data science and advanced analytics for large manufacturing and retail company. Employ Artificial Intelligence and Machine Learning techniques across all business channels, customer and consumer segments, markets and products. Pursue use cases to analyze and drive revenue, lower costs, increase speed, and reduce risk. Use Databricks to transform raw data into cognizable information. Use statistical analysis and advanced machine learning techniques to build descriptive, diagnostic and predictive models. Use ML Ops to deploy models. Use PowerBI for business reporting and dashboards to enable decision making. Evaluate implications of findings on business outcomes, and communicate and document work. Use Python and SQL to model real-world outcomes. Employ PySpark for distributed data processing on the Cloud. Use Agile methodology for continuous improvement and development. #LI-DNI

Position requires a Master’s degree in Business Analytics or an equivalent field, and 2 years of experience as a  Data Scientist. Proficiencies must include a minimum of: experience with Power BI; experience with Databricks; experience with Supervised and Unsupervised Machine Learning; experience with SQL; experience with Python; experience with PySpark; experience with  Statistical Analysis; experience with Predictive Analysis; and experience with Agile Methodology. #LI-DNI 

Job location: Draper, UT.

Alternatively, please send your resume, cover letter, and a copy of the ad to: Amber Ivie, 12634 South 265 West, Draper, UT 84020.