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Data Scientist Machine Learning Jobs in Utah (NOW HIRING)

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences ... We build systems that can learn from sparse and noisy data, emulate expensive physics simulations ...

Swire Coca-Cola, USA

Data Scientist

Draper, UT · On-site

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

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences ... We build systems that can learn from sparse and noisy data, emulate expensive physics simulations ...

Waystar

Data Scientist

Lehi, UT · On-site

... machine learning and analytical systems applied to design information and user behavior. • Works closely with Application Engineering teams to gather and process data, as well as in surfacing ...

Snap Finance

Data Scientist

West Valley City, UT · On-site

... machine learning programming languages such as R or Python. • Strong SQL skills and the ability ... data science projects from development to production. • Skilled analyst who produces regular ...

MasterCard

Senior Data Scientist

Holladay, UT · On-site

Workplace Python coding experience, including a good knowledge of the principal Python Data Science / Machine Learning (ML) library ecosystem. Excellent written and oral communication skills for both ...

Varsity Tutors

Machine Learning Tutor

Provo, UT · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Logan, UT · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Spanish Fork, UT · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Cedar City, UT · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

BILL

Senior Machine Learning Engineer

Draper, UT

$97K - $134K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Collaborate cross-functionally with product managers, engineers, and data scientists to translate ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$114K - $151K/yr

As a Senior Machine Learning Engineer, you will design, build, and deploy machine learning ... and data scientists to translate business requirements into scalable ML solutions • Analyze ...

Zions Bancorporation

Applied AI Scientist

Midvale, UT · On-site

As an Applied AI Scientist , you will collaborate with the Enterprise Data Analytics team to ... Discover, clean, and transform data for analysis * Design and build analytical and machine learning ...

Zions Bank

Applied AI Scientist

Midvale, UT · On-site

As an Applied AI Scientist , you will collaborate with the Enterprise Data Analytics team to ... Discover, clean, and transform data for analysis * Design and build analytical and machine learning ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Utah

Data Scientist Machine Learning information

See Utah salary details

$34.1K

$111.7K

$178.9K

How much do data scientist machine learning jobs pay per year?

As of Jun 26, 2026, the average yearly pay for data scientist machine learning in Utah is $111,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,700.00 and $123,800.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is ML a high paying job?

Data Scientist Machine Learning roles are generally well-paid due to the specialized skills required, such as programming in Python or R and knowledge of algorithms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for expertise in machine learning and data analysis.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require advanced analytical skills, domain expertise, and the ability to interpret complex models. Jobs that involve creative thinking, emotional intelligence, and tasks requiring human judgment—such as healthcare professionals, educators, and skilled trades—are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Utah? The most popular types of Data Scientist Machine Learning jobs in Utah are:
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Data Scientist Machine Learning jobs near you

Senior Machine Learning Scientist

Zanskar

Salt Lake City, UT • On-site, Remote

$88K - $121K/yr

Full-time

Posted 5 days ago

Job description

Role Overview 
Title: Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences)
Hours: Full-Time, Salaried
Location: Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote)
Benefits Eligible: Yes
Manager: Head of Reservoir R&D
 
Why we exist
Geothermal energy is the most abundant renewable energy source in the world. There is 2,300 times more energy in geothermal heat in the ground than in oil, gas, coal, and methane combined. However, historically it’s been hard to find and expensive to develop. At Zanskar, we’re building technology to find and develop new geothermal resources in order to make geothermal a cheap and vital contributor to a carbon-free electrical grid.
 
To do that, we combine deep subsurface expertise with advanced AI technologies—including modern machine learning, scalable scientific computing, and uncertainty-aware modeling—to dramatically improve geothermal discovery and development outcomes. We build systems that can learn from sparse and noisy data, emulate expensive physics simulations, and help teams make faster, higher-confidence decisions about where to drill and how to develop fields.
 
Who you are
You will help build the modeling and decision-making core of Zanskar’s geothermal exploration software. This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will:
Explore: you’re open-minded about methods and will prototype, benchmark, and iterate across approaches.
Reproduce & adapt: you can implement ideas from papers and new frameworks quickly, then harden the best ones into reliable workflows.
Decision-minded: you care about end-to-end outcomes (value, risk, time-to-decision), not just model accuracy.
Uncertainty-first: you build models that are accurate, well-calibrated, and dependable under distribution shift and sparse data regimes.
Collaborative: you work well with domain experts and can translate between geology/engineering intuition and ML systems.
 
What you’ll do
Build fast, reliable models that emulate or augment computationally expensive physics-based simulations (e.g., reservoir, wellbore, and coupled multi-physics workflows).
Evaluate and compare multiple modeling approaches (physics-informed, operator learning, transformers, diffusion models, etc.), establishing strong baselines and selecting methods based on evidence.
Build multi-step decision systems for exploration and appraisal: POMDP-style planning and belief-space decision making to recommend exploration steps.
Translate scientific and engineering questions into well-defined learning and decision problems: inputs/outputs, constraints, boundary/initial conditions, reward/cost structure, and success metrics (e.g., expected NPV, probability of success, downside risk).
Prototype, benchmark, and iterate across approaches (POMDP solvers, RL methods, VOI-style baselines, MPC-style replanning), then harden the best ones into reliable workflows and APIs.
Collaborate deeply with geoscientists, reservoir engineers, and software engineers to integrate these models and policies into production software.
 
What we’re looking for
3+ years of applied ML experience, ideally in scientific ML, decision-making under uncertainty, surrogate modeling, robotics/control, or related engineering/science domains.
Expertise in python and modern ML tooling (PyTorch preferred).
Track record of taking models from prototype → rigorous evaluation → adoption by technical stakeholders.
Strong fundamentals in probability/statistics and comfort with messy, real-world scientific datasets.
Experience building or using surrogate models for expensive simulators (PDE-driven systems, multi-physics, or similar).
Relevant technical strengths
Surrogate modeling. 
Sequential decision-making under uncertainty and reinforcement learning. 
Software engineering: Git, code review, reproducibility, CI basics, Docker/container workflows.
Experience with diffusion models.
Exposure to subsurface modeling domains: geothermal, oil & gas, CCS, hydrogeology, geoscience, or related.
Familiarity with cloud infrastructure and data systems (SQL, object storage, orchestration).
 
Location and Benefits
This position is based out of our headquarters in Salt Lake City, Utah, and is hybrid.
Benefits include:
Paid holidays
15 days PTO + PTO accrual increase based on tenure
Medical, dental and vision coverage
401k 
Stock options
Growth opportunities at a company with a direct impact in displacing carbon emissions
Equal Opportunity Employer 
 
Zanskar is an equal-opportunity employer and complies with all applicable federal, state, and local fair employment practice laws.