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About This Role
Working at the Naval Nuclear Laboratory we foster pride in belonging to an organization whose culture is made up of these core values: Trust, Empowerment, and Collaboration. Our company promotes a positive culture while ensuring the safety and reliability of our nation's naval nuclear reactors, and training the Sailors who operate those reactors in the U.S. Navy's submarines and aircraft carrier Fleets. Looking for a lifetime career? Apply today!
Job Description
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The Naval Nuclear Laboratory is seeking a Data Scientist to join a team dedicated to collecting and transforming data from the Naval Nuclear fleet for analytics throughout the Laboratory. Help turn complex nuclear data into powerful insights that drive innovation, safety, and long?range strategic impact. The successful candidate will be responsible for building predictive models to characterize various systems, presenting in\-depth analysis in a clear and concise manner with a data\-oriented approach to problem solving and decision making. In addition, you will display great collaboration and interpersonal skills, both written and verbal through leading improvement projects and providing regular updates to the organization.
Required Combination of Knowledge and Skill
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Bachelors degree from an accredited college or university in a related engineering or science field and a minimum of 4 years of relevant experience; or Masters degree from an accredited college or university in a related engineering or science field and a minimum of 2 years of relevant experience; or Doctorate degree from an accredited college or university in a related engineering or science field.
Preferred Skills
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- Good scripting and programming skills, experience in Python.
- Experience with data visualization packages, such as Tableau.
- Understanding of machine\-learning and its applications.
- Understanding of RAG or embedding\-based search.
Compensation and Benefits
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- Health, Dental, Vision \& Voluntary Benefits
- Disability, Life \& Accident Insurance
- 401(k) Savings program \& Capital Accumulation Plan
- Personal \& Medical Time Off
- Paid Parental Leave
- Flexible Work Schedules
- Tuition Assistance for Eligible Employees
- Student Debt Benefit Personal Time Off Sell Program
- Employee Assistance Program (EAP)
- Wellness Program
- Visit us online to view all NNL benefits!
Pay Range
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$95,700\.00 \- $149,600\.00 annually
Salary information provided is a general guideline only. Annual salary is based upon candidate experience and qualifications, as well as market and business considerations.
The Naval Nuclear Laboratory is operated for the U.S. Department of Energy (DOE) by Fluor Marine Propulsion, LLC (FMP), a wholly owned subsidiary of Fluor Corporation. Naval Nuclear Laboratory personnel are FMP employees who work at four DOE facilities: Bettis Atomic Power Laboratory, Knolls Atomic Power Laboratory, Kenneth A. Kesselring Site, and Naval Reactors Facility, and at the U.S. Department of Defense\-owned Nuclear Power Training Unit\-Charleston. FMP employees also have an established presence at numerous shipyards and vendor locations. For nearly 70 years, the Naval Nuclear Laboratory has developed advanced nuclear propulsion technology, provided technical support, and trained world\-class nuclear operators to ensure the safe and reliable operation of our nation's submarine and aircraft carrier Fleets. The Naval Nuclear Laboratory is a national asset solely dedicated to the Naval Nuclear Propulsion Program. We rely on the dedication and innovation of our nearly 8000 engineers, scientists, technicians, and support personnel.
All candidates must be U.S. citizens. Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter. FMP is a government contractor and maintains a drug free workplace and workforce. All candidates must be able to pass a drug test in compliance with FMP company policy and 10 CFR 707\. Marijuana is a Federal Schedule I controlled substance and illegal under Federal Law. Therefore, FMP is required to test for marijuana.
Fluor Marine Propulsion, LLC is an Equal Opportunity Employer, including disability/vets. All qualified applicants will receive consideration for employment without regard to race, color, age, sex, religion, national origin, disability, veteran status, genetic information, or any other criteria protected by federal, state, or local law.
Salary Context
This $95K-$149K range is in the lower quartile for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Naval Nuclear Laboratory, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 789 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($122K) sits 36% below the category median. Disclosed range: $95K to $149K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Naval Nuclear Laboratory AI Hiring
Naval Nuclear Laboratory has 1 open AI role right now. They're hiring across Data Scientist. Based in Niskayuna, NY, US. Compensation range: $149K - $149K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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