at the right time to serve our customers. We are the backbone of our expert supply strategy, driving operational excellence through data- driven planning and execution. We work closely with finance, operations, product,…
Engineering & IT · Tucson, AZ
Data Scientist jobs in Tucson, AZ
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
421
Open roles today
$36–$90/hr
Typical pay range
$122k
Median, full-time
8
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Open data scientist roles
12 shown of 421 · sorted by freshness
About the job Remote Data Analyst / HR The Nations 2nd largest Technical Staffing and Services Firm, has an opening for a Remote Analyst at a global leader in retail pharmacy for a 6‑month contract with the opportunity f…
A leading open-source software firm is seeking a Junior Software Developer to join their Observability team. This remote role requires strong skills in Python and Go, along with a passion for open-source technologies, Li…
and their impact to HR, Benefits, and Payroll teams • Troubleshoot complex system issues and perform audits/validations to ensure data integrity • Develop and execute test plans and audit processes; secure business sign-…
About the job Data Entry Associate - Remote Position Overview Apex Dental Data Entry Associate usually put skills to work by supporting our client through document review and data entry. Your work will make a positive di…
TEKsystems is seeking a Live Expert Service Desk Analyst to provide first and second line technical support for internal employees. The role involves analyzing and resolving issues across software, hardware, and connecti…
career wherever you want it to go. Join EY and help to build a better working world. Ethics and Compliance Investigations Team – Data, Time & Expense Senior Associate At EY, you will have the chance to build a career as…
Job Description Job Description The Data Analyst plays a crucial role in gathering, interpreting, and transforming data into actionable insights to support business decision-making. This position involves analyzing compl…
$86.8k - $165.2k
creating a safer, more secure world. Join us and help shape the future of aerospace and defense. We are hiring a Principal Analyst Data Manager to work onsite in Tucson, Arizona. What You Will Do Identifies all data deli…
$101k - $124k
similarly motivated electrical engineers, mathematicians, computer scientists, and analysts who are collectively responsible for creating... ...databases, sources, methodologies, and analytical tradecraft, extract data r…
$120k - $145k
Discover your future with us. We are seeking a mid-level Scientist (Algorithm Developer) with a strong background in Math, Physics... ...processing algorithms and software. In this position you will analyze data, evaluat…
Cross-Functional Excellence : Collaborate with brilliant computer scientists, electrical engineers, and mathematicians in a true R&D... ...Systems: Design and architect AI solutions that process real-world data at scale…
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What data scientists earn in Tucson
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$50 | $75k–$103k |
| Mid level | $50–$68 | $103k–$141k |
| Senior | $65–$90 | $136k–$188k |
Adjusted for the Tucson 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
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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.
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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
04
Staff Data Scientist
05
Head of Data Science
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