$150k - $200k
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…
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.
607
Open roles today
$45–$113/hr
Typical pay range
$153k
Median, full-time
7
Fresh in this list
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01
Open data scientist roles
12 shown of 607 · sorted by freshness
$168.8k - $253.25k
Analytics Operations role is a unique opportunity to help shape how data and AI drive decision-making across Insulet as the company... ...Intelligence, Analytics and Advanced Algorithms, you will mentor Data Scientists o…
$149.8k - $262.2k
meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500 work smarter, faster, and…
$149.8k - $262.2k
meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500 work smarter, faster, and…
We are looking for an experienced Identity & Access Management Analyst to support a long-term contract opportunity within the insurance industry in San Diego, California. This role focuses on strengthening identity gover…
culture, then you want to be a part of the Xenith Solutions family. Xenith Solutions is seeking a highly skilled and motivated Data Scientist to join our team in developing innovative solutions to challenging national pr…
$43.14 per hour
THOR Solutions is seeking a Senior Data Visualization Developer with strong experience with both Power BI and Tableau to support NIWC Pacific in San Diego, CA . The selected candidate will develop and maintain business a…
as one team. - We Care Deeply : We show up with integrity, kindness, and respect for one another. The Position The Senior Manager, Data Engineering will manage an engineering team responsible for building and operating V…
$85k - $100k
Data Engineer The Marlin Alliance is seeking a dedicated Data Engineer to support our Navy client. The successful candidate will support a DoD client program by designing, building, and maintaining data pipelines that tr…
$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…
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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.
05
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.
03
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.
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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