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Remote Data Scientist Machine Learning Jobs in Utah

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... We build systems that can learn from sparse and noisy data, emulate expensive physics simulations ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88K - $121K/yr

Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote) Benefits Eligible: Yes Manager ... We build systems that can learn from sparse and noisy data, emulate expensive physics simulations ...

Humana

Lead Data Scientist

North Salt Lake, UT · On-site +1

Lead and oversee the development of advanced machine learning models, ensuring their seamless ... per week remote/home. Office Location Options: * Louisville, KY * Boston, MA * New York, NY

Varsity Tutors

Machine Learning Tutor

Logan, UT · Remote

$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

Provo, UT · Remote

$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

$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

$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

Data Science Tutor

Logan, UT · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Cedar City, UT · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Provo, UT · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

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All JobsRemote Data Scientist Machine Learning JobsRemote Data Scientist Machine Learning Jobs in Utah

Remote Data Scientist Machine Learning information

What does a Remote Data Scientist specializing in Machine Learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

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

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

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

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.
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:
What are popular job titles related to Remote Data Scientist Machine Learning jobs in Utah? For Remote Data Scientist Machine Learning jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist Machine Learning jobs in Utah look for? The top searched job categories for Remote Data Scientist Machine Learning jobs in Utah are:
What cities in Utah are hiring for Remote Data Scientist Machine Learning jobs? Cities in Utah with the most Remote Data Scientist Machine Learning job openings:
Remote 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 27 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.