Wed, 07/29/2026 - 06:04 Job Description Summary The Sr Data Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and consultancy development env…
Engineering & IT · Salt Lake City, UT
Data Scientist jobs in Salt Lake City, UT
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
513
Open roles today
$39–$99/hr
Typical pay range
$134k
Median, full-time
5
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open data scientist roles
12 shown of 513 · sorted by freshness
$104k - $123.5k
adaptability. We foster a psychologically safe environment centered on trust and accountability where feedback is encouraged. We leverage data to reflect on progress, own setbacks, celebrate successes, and continuously i…
$90k - $130k
This Jobot Job is hosted by Anastasia Young. BIM and Data Center Experience Required - 100% Remote in Mountain or Central Timezones Salary: $90,000 - $130,000 per year A Bit About Us We are a top and growing National pro…
$72k - $115k
set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist I Who is Mastercard? As a global technology company our mission at Mastercard i…
$70.8k - $123.8k
frameworks * Work with Model Context Protocol (MCP) servers and related tools to integrate AI applications with enterprise systems and data sources * Containerize applications using Docker and support deployment in Kuber…
want to shape the mobility of tomorrow with us. Are you ready to achieve great things with us? HOW YOU CAN MAKE AN IMPACT The Data Analyst is responsible for collecting, analyzing, and interpreting manufacturing and supp…
Role Overview Title: Full-Stack Software Engineer, Platform Data Hours: Full-time; salaried Location: Salt Lake City, UT (... ...that put that data in front of the geoscientists, engineers, data scientists, and operators…
$79.6k - $139.3k
Senior Data Engineer (Databricks & Cloud Analytics) Position Description Are you passionate about building modern data platforms... ...will partner with solution architects, business analysts, data scientists, and client…
Job Description Job Description Junior AI Engineer Job Type: Permanent Full Time Location: Salt Lake City, Utah, United States How you'll make an impact • Design and develop AI-driven product features using ML, GenAI, an…
$130k - $170k
You'll be at the forefront of applied AI, designing and shipping agentic systems that operate autonomously, reason across complex data, and deliver world-class experiences to TaxBit's enterprise customers. We welcome ind…
Job Description Job Description Description: Data Scientist Location: Murray, Utah Work Arrangement: In-Office / Hybrid About the Role We're looking for a Data Scientist to join Bear River Mutual Insurance. As a Data Sci…
$140k - $231k
products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data Scientist Who is Mastercard? Mastercard is a global technology company in the payments indu…
02
What data scientists earn in Salt Lake City
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $39–$54 | $82k–$113k |
| Mid level | $54–$74 | $113k–$154k |
| Senior | $72–$99 | $149k–$206k |
Adjusted for the Salt Lake City market from national ranges.
03
What employers ask for
The skills these listings keep naming
Python (pandas, scikit-learn)SQLStatistics and A/B testingMachine learning fundamentalsData visualizationExperiment designCommunicating with stakeholdersDomain and product sense
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through a data project that changed a decision.
Structure it as question, approach, finding, action. Projects that ended in a decision — even 'we did not launch' — beat technically impressive analyses that went nowhere.
How would you design an A/B test for a new feature?
Cover the metric, randomization unit, sample size, and duration, plus a pitfall like peeking or interference. Practical rigor is what is being tested.
Your model performs well offline but poorly in production. Why might that be?
Discuss train/serve skew, data leakage, distribution shift, and feedback loops. Listing several plausible causes and how you would check each is the strong answer.
Explain p-values or confidence intervals to a non-technical stakeholder.
Use plain language and a concrete scenario, and resist overstating certainty. They are testing whether your statistics survive translation.
How do you handle missing or messy data?
First ask why it is missing — the mechanism matters more than the imputation method. Then discuss options and how the choice affects conclusions.
When would you not use machine learning for a problem?
When a rule, a query, or a simple heuristic wins on cost and interpretability. Knowing when ML is overkill signals maturity.
How do you decide which metric a team should optimize?
Talk about proxy versus true goals, gameability, and counter-metrics. A story about a metric that backfired is very effective here.
05
Resume tips that move the needle
For data scientists specifically — generic advice costs you here
01
Lead every bullet with the business result — revenue, retention, cost — and put the method second.
02
Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
03
Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
04
Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
05
Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
06
Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
Ten quiet minutes a day
Applying for data scientist jobs in Salt Lake City?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.