Job Title: Data Scientist Location: San Deigo CA, NJ, Boston MA or Dallas TX-On-site Role Overview We are seeking highly analytical and outcome-driven Data Scientists to translate business questions into testable hypothe…
Engineering & IT · San Diego, CA
Data Scientist jobs in San Diego, 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.
565
Open roles today
$45–$113/hr
Typical pay range
$153k
Median, full-time
1
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Open data scientist roles
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tangible. ABOUT THE ROLE This role builds and operates the data and machine-learning infrastructure the platform runs on: the... ...that make these workflows reliable and easy for engineers and scientists to use. WHAT WE…
$150k - $170k
Lead Data Scientist - Growth & Marketing Models AI-first targeting and decision models that move real money | Lean, AI-leveraged team | Senior/Lead level Office Locations: San Diego, CA (La Jolla/UTC) or Atlanta, GA (Cum…
$100k - $130k
Sigma Defense is seeking a Data Engineer to join our team in San Diego NB, CA. This is a contingent position that is pending award... ...models. Collaborates with database engineers and other scientists to develop, refin…
$185.5k - $251k
Overview Join the Intuit Customer Success Data Science & Analytics team as a Staff Data Scientist focused on the Voice of the Customer (VoC). In this role, you will define how customer feedback shapes strategy by connect…
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate... ...to make their businesses more profitable. As a Senior Data Scientist at the Experian I…
Data Developer (Hybrid | Secret Clearance Required) Company: Innovatus Technology Consulting Client: U.S. Navy / Naval Information Warfare Systems Command (NAVWAR) Location: San Diego, CA (Hybrid – 1-2 days per week onsi…
$110k - $180k
The Marlin Alliance, Inc. is seeking a Senior Data Engineer (OpAI) to design, build, and operationalize advanced data pipelines and... ...years of experience as a business analyst, data analyst, data scientist, data engi…
$175k - $225k
The Marlin Alliance is seeking a forward-thinking Data Engineer in San Diego, CAto provide client support to our Navy client. This... ...' experience working as a business analyst, data analyst, data scientist, data engi…
$175k - $200k
The Marlin Alliance is seeking a forward-thinking Data Engineer/Data Architect in San Diego, CAto provide client support to our... ...assurance process. Work closely with data analysts and data scientists to ensure data…
Staff Data Engineer Location: Remote Are you tired of being kept in a restricted creative box with limited autonomy to push boundaries and ideas to solve problems with Data products? Or not seeing your work directly impa…
$109k - $191k
application process for external applicants . JOB DESCRIPTION AND POSITION REQUIREMENTS: We are seeking highly skilled and motivated Data Science Engineers to join our DevSecOps Department/Cyber, Modeling and Simulation…
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What data scientists earn in San Diego
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $45–$62 | $94k–$130k |
| Mid level | $62–$85 | $130k–$177k |
| Senior | $82–$113 | $171k–$236k |
Adjusted for the San Diego 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.
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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
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Junior Data Scientist
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Data Scientist
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Senior Data Scientist
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Staff Data Scientist
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Head of Data Science
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