critical infrastructure that supports the digital age and shapes the spaces where people work, connect, and thrive. From high-performance data centers driving the future of AI to dynamic commercial environments, your wor…
Engineering & IT · New Orleans, LA
Data Scientist jobs in New Orleans, LA
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
186
Open roles today
$36–$90/hr
Typical pay range
$122k
Median, full-time
11
Fresh in this list
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01
Open data scientist roles
12 shown of 186 · sorted by freshness
$71.3k - $140.6k
clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. Work you'll do As a PROJECT - Data Engineer II on the AI & Data team, you will be responsible for… Designing, de…
We are seeking an AI Data Integration Engineer with strong hands-on experience in Snowflake, healthcare claims data, and practical AI/LLM integration. This role will lead the creation of a sanitized claims data layer (Sn…
to learn how you could help make great things possible not only in your community, but around the world. HDR is currently seeking a Data Center Project Manager to join one of the largest, fastest growing, and comprehensi…
$83.6k - $125.4k
Job ID: 44157Reference: 300016272956432Location: Baton Rouge, LA, United States | New Orleans, LA, United States | Metairie, LA, United StatesDepartment: Structural EngineeringBusiness Unit: ANA United StatesWork Type: H…
$82.6k - $162.8k
governance, risk, and compliance tools, identity and access management solutions, security information and event management platforms, or data loss prevention solutionsExperience with cloud platforms such as Amazon Web S…
$134.5k - $265.1k
relevant artifacts related to development and testing, and ensure process compliance on Maximo development and testing processesPerform data loads using MIF or MXLoader to MaximoTroubleshoot issues in production environm…
$163.4k - $322.1k
sponsorship, now or at any time in the future. Preferred Functional knowledge of MS D365 F&O ERP processes and systemsDynamics 365 solution data modelData migration tools and processes within Dynamics 365Experience with…
$118.7k - $243.7k
Work you’ll do Assist in the design, implementation, and sustainment of zero trust architectures to safeguard critical assets and data against emerging cyber threats.Serve as the subject matter expert (SME) for applicati…
exciting opportunity to contribute to impactful projects along the Texas coast while collaborating with a team of leading engineers, scientists, and modelers.About the RoleIn this role, you will support and lead the anal…
Engineering plans, specifications, and design calculationsTechnical reports, memos, and client deliverablesCollect, analyze, and present data to clients, stakeholders, and in public forumsManage and mentor multidisciplin…
$85.39k - $116.98k
Syms Strategic Group (SSG) is seeking a talented Senior Systems Engineer (Amazon Web Services (AWS) Data Engineer) - II Location: Remote Department: Veterans Affairs (VA) Type: Full Time Min. Experience: Experienced Secu…
02
What data scientists earn in New Orleans
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$50 | $75k–$103k |
| Mid level | $50–$68 | $103k–$141k |
| Senior | $65–$90 | $136k–$188k |
Adjusted for the New Orleans market from national ranges.
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.
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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.
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
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Staff Data Scientist
05
Head of Data Science
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