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-…
Engineering & IT · Fresno, CA
Data Scientist jobs in Fresno, CA
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
219
Open roles today
$37–$91/hr
Typical pay range
$124k
Median, full-time
4
Fresh in this list
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01
Open data scientist roles
12 shown of 219 · sorted by freshness
A data services company is seeking a Junior Data Entry Operator to work remotely. The role involves inputting data from paper documents into digital spreadsheets, updating order statuses for customers, and ensuring accur…
organizational goals. TECHNICAL SKILLS: Proficient in HRIS platforms and Microsoft Office Suite with the ability to manage employee data, reporting, and documentation accurately. Excellent verbal and written communicatio…
creation, password management, new computer setup, alert monitoring and response, gather information and troubleshoot client issues. Data restoration. Maintain internal technical documentation. Monitor and document the s…
$80k - $110k
decision-makers, and team players. Compensation: $80,000 - $110,000 yearly Responsibilities: Help shape decision-making through data- driven recommendations on strategic planning, business administration, and the annual…
$130k - $140k
releases. ~ Strong functional expertise in Order Management, Purchasing, and Inventory modules. ~ Foundational knowledge of master data, Account Receivables, and e-commerce. ~ Working technical knowledge of Oracle ERP ar…
$17 per hour
As a data entry employee, you will be performing routine data entry tasks under close supervision. Your efforts will help ensure our client's database is maintained with updated account information by verifying, reviewin…
Tier 2 Help Desk Technician (Hybrid) – Fresno, CA Grapevine MSP is expanding again, and we are seeking a skilled Tier 2 Help Desk Technician to join our team. If you excel at solving complex technical issues, enjoy colla…
$83.6k - $145k
Do you thrive in an imaginative and inventive environment? Are you someone who flourishes when part of a cohesive team where collaboration and ideas flow freely? Want to work for a firm that is taking concrete actions to…
$90.1k - $115.2k
Do you thrive in an imaginative and inventive environment? Are you someone who flourishes when part of a cohesive team where collaboration and ideas flow freely? Want to work for a firm that is taking concrete actions to…
$38 per hour
and maintain security of LANs. Work with multiple hardware and software platforms. Ensure the integrity and security of enterprise data on host computers, multiple databases. Practice network asset management, including…
Job Description Job Description Clinica Sierra Vista is excited to be one of the largest Federally Qualified Health Centers in the Nation! We’re honored to serve the men and women of the fields. We also offer care and su…
02
What data scientists earn in Fresno
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$50 | $76k–$104k |
| Mid level | $50–$68 | $104k–$142k |
| Senior | $66–$91 | $138k–$190k |
Adjusted for the Fresno 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.
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.
04
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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