$71.3k - $140.6k
clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. Work you'll do As a PROJECT - Data Engineer II on the AI & Data team, you will be responsible for… Designing, de…
Engineering & IT · Las Vegas, NV
Data Scientist jobs in Las Vegas, NV
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
438
Open roles today
$38–$96/hr
Typical pay range
$130k
Median, full-time
5
Fresh in this list
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01
Open data scientist roles
12 shown of 438 · sorted by freshness
analytical support, delivering insights that drive profit, and being a reliable business partner for Gaming operations. The role leverages data to identify trends, measure business performance, and provide actionable ins…
Requisition ID: 14860ERP Eligible?: YesERP amount: $50 LMRecognitionRelocation: NoType: ExemptShift: 1Clearance Prior to Start: SecretFinal Clearance: TS/SCIPay Transparency: $70,500.00 - $130,900.00Experience Level: Exp…
$168k - $170k
North Las Vegas, Nevada • Job Type: Direct Hire • Posted: 3 days agoEnterprise Data & AI ArchitectOur client has built an enterprise intelligence platform on Microsoft Fabric that spans multiple operating entities and su…
vendors, management etc. in both formal and informal situations.An analytical mindset that thrives on formulating strategy and presenting data. Highly organized with a strong sense of urgency.Additional RequirementsPosit…
a global network of experts – planners, designers, engineers, scientists, consultants, program and construction managers – leading the change... ...~4 or more years of relevant engineering experience. ~ Prior data center…
$149k - $198.5k
Mission Summary: The Data Platform team is the vital link between our company's expansive data and the engineering teams that rely on it. We architect and operate the core services and infrastructure necessary to transfo…
Lead Data Engineer - Delivery Lead On-site in Las Vegas Nevada. About the job you're considering The Delivery Lead will oversee the end-to-end delivery of a Teradata-to-Azure/Databricks migration powering client's next-g…
At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge case…
$149k - $198.5k
Mission Summary: We are seeking a Senior Engineer to join our ML Data Services team and help us build and improve data infrastructure for Autonomy ML teams. As a Senior Engineer, you will be responsible for building scal…
company that champions growth and development? Join a global digital infrastructure services provider supporting network operators, data centers, wireless networks, and subsea infrastructure across more than 90 countries…
$119.66k - $122k
Sripadha Inc., a Las Vegas, NV based IT Consulting Services Firm has multiple openings for JOB ID 11335: Data Engineer. Job duties include: Design, develop, and operate high-scale applications focusing on operational exc…
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What data scientists earn in Las Vegas
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$53 | $80k–$110k |
| Mid level | $53–$72 | $110k–$150k |
| Senior | $70–$96 | $145k–$200k |
National ranges — pay in Las Vegas typically tracks these.
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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.
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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.
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Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
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Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
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Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
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Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
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Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
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Staff Data Scientist
05
Head of Data Science
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