$104k - $208k
Salary: $104,000 - 208,000 per year Requirements: We require native or bilingual-level fluency in English. We require proficiency in at least one programming language or framework, such as JavaScript, TypeScript, Python,…
Engineering & IT · Oklahoma City, OK
Data Scientist jobs in Oklahoma City, OK
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
249
Open roles today
$34–$86/hr
Typical pay range
$116k
Median, full-time
6
Fresh in this list
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01
Open data scientist roles
12 shown of 249 · sorted by freshness
subsystems that supports the BDS mission delivering a highly capable solution comprised of three core bedrocks to include Production Data Management (PDM), Enterprise Resource Planning (ERP), and Manufacturing Execution…
leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global de…
$154.9k - $225.3k
industry events or webinars and supporting enterprise or partner/channel sales motions. Why Cisco? At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond.…
Reference: 85347-3701685-D Systems, a KRATOS Company, is seeking a highly motivated candidate who will provide full lifecycle systems engineering technical contribution and leadership in support of unmanned aircraft prog…
A Manufacturing/ distribution company is looking for a Data Engineer with 3 + years of experience to join a dynamic team in Oklahoma City, Oklahoma. In this role, you will play a crucial part in designing and maintaining…
$50 - $70 per hour
Job Title: Senior Data Engineer Location: Oklahoma City, OK Pay: $50 - $70 / Hour Work Schedule: Hybrid — 4 days onsite and 1 day remote initially Benefits: This position is eligible for medical, dental, vision, and 401(…
$100k - $200k
Job Title: Sr. Data Developer Industry : Energy / Oil & Gas Location (city, state): Oklahoma City, OK Assignment Type: Contract Pay: $100,000 - $200,000 / year depending on experience. Work Schedule : Monday – Friday, 8-…
$90k - $100k
Opportunity to support a mission-driven healthcare services organization Strategic role focused on business analysis, enterprise data strategy, and data visualization initiatives Partner with leadership and multiple busi…
$80k - $90k
between internal business teams, external partners, and technology stakeholders. This highly visible role combines business analysis, data analytics, reporting, process improvement, partner management, and workflow optim…
$110k - $125k
Please contact us today to discuss this opportunity! Overview: Our client is seeking a Senior Database Engineer to join a growing data and business intelligence team. This role will be responsible for designing, optimizi…
Database Architect / Administrator We’re looking for someone to join our team with at least five years of experience in relational databases and a minimum of two years of experience in SQL Server. Essential duties and re…
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What data scientists earn in Oklahoma City
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $34–$47 | $71k–$98k |
| Mid level | $47–$64 | $98k–$134k |
| Senior | $62–$86 | $129k–$178k |
Adjusted for the Oklahoma City 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
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.
05
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
04
Staff Data Scientist
05
Head of Data Science
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