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Engineering & IT · Raleigh, NC
Data Scientist jobs in Raleigh, NC
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
762
Open roles today
$38–$95/hr
Typical pay range
$129k
Median, full-time
9
Fresh in this list
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01
Open data scientist roles
12 shown of 762 · sorted by freshness
$104.9k - $174.7k
Salary: $104,900 - 174,700 per year Requirements: Substantial experience in a senior data scientist role Experience leading complex projects and customer relationships Significant experience leading technical teams Exper…
$104.9k - $174.7k
10+ years of engineering experience, along with experience in data strategy and data management. A bachelors degree is preferred... ...approach. Our team includes more than 2,000 technologists, data scientists, and exper…
$118.3k - $219.8k
We require some management experience, including leading a team directly or indirectly. We need substantial experience in a Data Scientist role. We look for experience leading complex projects and managing customer relat…
$115.4k - $192.3k
such as BERT, RoBERTa, and T5. We expect proficiency with big data platforms and tools such as Hadoop, Spark, or AWS. We value... ...skills, with the ability to guide and support junior data scientists and work across fu…
$94.69k - $122.54k
included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description AI/ML Data Engineering Specialist, US Commercial As part of our enterprise AI strategy to spe…
you to grow and excel.Job DescriptionIn the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as... ...Interest GroupInfosys Limited Salary Min73000Salary Max122275Job RoleData Science C…
$122k - $145k
acceptance criteria* Create process maps that demonstrate a client’s business workflows to assist in stakeholder alignment* Capture data, reporting, security, and user experience needs at a functional level* Validate req…
$125k - $150k
Job Id: 166594Job Location: Raleigh, North CarolinaSecurity Clearance: No ClearanceBusiness Unit: Piper CompaniesDivision: EnterprisePosition Owner: Jackie AllenPiper Companies is seeking an Azure Engineer for a world le…
Job Summary (List Format): - Serve as Data Engineer for DHHS-ITD, focusing on the design, development, and optimization of cloud-based analytics environments. - Build and maintain scalable ETL/ELT data pipelines using Az…
Job Summary (List Format): - Serve as a Data Engineer focused on quality assurance, quality checking, and ETL processes - Ensure accuracy and integrity of data transferred from shared file transfer services to S3 buckets…
Project Details: This Sr. Engineer is responsible for the design, architecture and deployment of data discovery and inventory platform. Requirements: ~10 years full-stack engineering experience (Must have experience in P…
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What data scientists earn in Raleigh
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$52 | $79k–$109k |
| Mid level | $52–$71 | $109k–$148k |
| Senior | $69–$95 | $144k–$198k |
Adjusted for the Raleigh 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
01
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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