critical infrastructure that supports the digital age and shapes the spaces where people work, connect, and thrive. From high-performance data centers driving the future of AI to dynamic commercial environments, your wor…
Engineering & IT · Omaha, NE
Data Scientist jobs in Omaha, NE
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
259
Open roles today
$36–$88/hr
Typical pay range
$120k
Median, full-time
11
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01
Open data scientist roles
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managers to lead the planning, design, documentation, and construction administration of multiple building types, from high-performance data centers that power cloud computing and the digital infrastructure the world rel…
Read further to learn how you could help make great things possible not only in your community, but around the world. In the role of Data Engineer II, we'll count on you to:Build and maintain batch and streaming ingestio…
$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…
semantic structures that promote reuse and consistent interpretation.Partner with analysts to translate business questions into durable data models.Implement models using layered patterns (raw/conformed/curated) and modu…
DescriptionAt HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas t…
DescriptionAt HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas t…
managers to lead the planning, design, documentation, and construction administration of multiple building types, from high-performance data centers that power cloud computing and the digital infrastructure the world rel…
mission and strategic initiatives. Key ResponsibilitiesBenefits Program Support and Administration:Support leadership by gathering plan data, analyzing trends, and identifying opportunities for consideration in plan desi…
DescriptionAt HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas t…
of enterprise integration solutions that enable secure, reliable, and scalable connectivity across business applications, platforms, data systems, and external partners.This role is responsible for establishing integrati…
world-class experience for both our clients and our team. As Milan continues to grow, so does the scale and sophistication of the data behind our business. We’re looking for a Senior Data Engineer who can help build the…
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What data scientists earn in Omaha
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$49 | $74k–$101k |
| Mid level | $49–$66 | $101k–$138k |
| Senior | $64–$88 | $133k–$184k |
Adjusted for the Omaha market from national ranges.
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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
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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
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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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