$89.8k - $229.3k
and marketing services driven by aggregated and de-identified data insights and award-winning creative services. Spectrum Reach helps... ...about Spectrum Reach can be found at the Lead Data Scientist, you are responsibl…
Engineering & IT
Data Scientist jobs
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
60,859
Open roles today
$38–$96/hr
Typical pay range
$130k
Median, full-time
11
Fresh in this list
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01
What data scientists earn in the US
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$53 | $80k–$110k |
| Mid level | $53–$72 | $110k–$150k |
| Senior | $70–$96 | $145k–$200k |
National ranges. City pages adjust for the local market.
02
Open roles across the US
11 shown of 60,859 · sorted by freshness
$110k - $160k
OverviewSteampunk wants you to join our awesome team as Power BI Data Visualization Engineer. In this role you'll be working with a large team of Steampunk and clients to identify data sources, tools, and mission challen…
do the same. No matter where you are in the world, this is your chance to be part of something exceptional.Job title: (Senior) Data Scientist / ConsultantLocation: Remote (USA)About the RoleAt Centric, we help some of th…
powerful? Join our outstanding team and help shape the future of energy.Position Specific DescriptionWe are seeking a hands-on Lead Data Engineer to architect and deliver enterprise-grade data and AI products that power…
Cyber/ Software Industry(ies): Consulting Services Our client is a specialist technical consultancy delivering bespoke technology and data solutions to solve complex operational challenges. Due to continued growth, they…
Inspire Brands is hiring a Lead Data and AI Engineer for the Enterprise Data Organization to design, build and manage data pipelines (Data ingestion, data transformation, data distribution, quality rules, data storage et…
$205.32k
CompanyCox Automotive - USAJob Family GroupEngineering / Product DevelopmentJob ProfileSr Lead Data EngineerManagement LevelSr Manager - Non People LeaderFlexible Work Option Hybrid - Ability to work remotely part of the…
workflows o Retrieval Augmented Generation (RAG) o Generative AI concepts • Familiarity with AI governance, explainability, and trusted data practices. ________________________________________ Oracle AI Experience • Expe…
Job-ID29304584Reference26-26003In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Database Engineering. Review and analyze complex multi-faceted…
$55 per hour
DescriptionKforce has a client in Altamonte Springs, FL that is seeking a Data/ Business Analyst - Engineering.Responsibilities:* Design, develop, and maintain scalable data pipelines supporting consumer intelligence and…
Job-ID27380861Reference26-03163Lead Data Scientist - Autonomous Goal ManagementJob Description SummaryThe Enterprise AI organization at client is a pioneering force, driving AI innovation across our Insurance and CenterW…
03
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
08
Data Scientist jobs by city
RemoteNew York, NYSan Francisco, CASan Jose, CALos Angeles, CASan Diego, CASacramento, CAFresno, CASeattle, WAPortland, ORDenver, COSalt Lake City, UTLas Vegas, NVPhoenix, AZTucson, AZAlbuquerque, NMBoston, MAPhiladelphia, PAPittsburgh, PAWashington, DCBaltimore, MDRichmond, VAChicago, ILColumbus, OHCleveland, OHCincinnati, OHDetroit, MIIndianapolis, INMilwaukee, WIMinneapolis, MNKansas City, MOSt. Louis, MOOmaha, NEHouston, TXDallas, TXFort Worth, TXAustin, TXSan Antonio, TXOklahoma City, OKAtlanta, GAMiami, FLTampa, FLOrlando, FLJacksonville, FLCharlotte, NCRaleigh, NCNashville, TNMemphis, TNLouisville, KYNew Orleans, LA
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