$51.75k - $69.75k
network and system administration tasks as assigned by the Director of IT. Ensure compliance with FirstLine’s technology policies and data security best practices. Work directly with and manage vendors as directed by Dir…
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.
264
Open roles today
$36–$90/hr
Typical pay range
$122k
Median, full-time
3
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Open data scientist roles
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Leadership Team Assessment ~Plan & lead assessment related professional development for leaders, teachers, staff, & parents/families - data driven instruction, data collection, analysis, & use, etc. ~Determine multiple m…
What You Need To Know Shape a remarkable future with us. Build a career working for an industry leader that truly invests in their people – and equips them with leading technology, continuous learning, and the ability to…
$22 - $24 per hour
Assurance programs and SOP’s and must be knowledgeable of both job-specific routine and complex analyses. The analyst validates and reviews data for accuracy, and uploads laboratory data into the LIMS that ultimately gen…
JOB SUMMARY/PURPOSE Serves as the enterprise authority for natural gas measurement operations and volumetric data governance across the utility system. Establishes system-wide measurement standards, provides final approv…
The Data Manager impacts students’ lives by: Working closely with the Directors of Curriculum and Instruction and the entire school leadership team to lead the use of academic performance data to highlight areas for impr…
JOB SUMMARY/PURPOSE The Tax Accounting Analyst supports the Company’s tax accounting and compliance processes across multiple jurisdictions. This position assists with the preparation, accrual, reporting, and payment of…
technical teams and business stakeholders to ensure project requirements are clearly understood. Analyze business and operational data to identify trends, anomalies, and opportunities for improvement. Create and maintain…
analyze billing and payment performance reports. Support internal and external audits by providing accurate billing and payment data. Collaborate with IT, regulatory and finance teams to implement system enhancements and…
We are looking for a Remote Business Analyst to identify business needs, analyze data, and propose efficiency improvements. The candidate will collaborate with stakeholders and IT teams to gather requirements, document p…
the form of reports, presentations, etc. • Compiles, codes, categorizes, calculates, tabulates, audits, or verifies information or data. • Ensures compliance with all brand established systems and procedures. • Creates a…
$75k - $110k
If you are a passionate Project Architect looking to join a growing firm, there is an incredible opportunity that awaits. This reputable Architecture and Design Firm is looking for a Licensed Architect to mentor, coach,…
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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.
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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.
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.
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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
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
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