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About This Role
Date: Oct 2, 2026
Location(s): Juno Beach, FL, US, 33408
Company: NextEra Energy
Requisition ID: 97819
NextEra Energy Resources is one of America’s largest wholesale electricity generators, harnessing diverse energy sources to power progress. We deliver tailored energy solutions that fuel economic growth, strengthen communities, and help customers achieve their energy goals. Ready to make a lasting impact? Take the next step in your career with us!
Position Specific Description
The Decision Science team within NextEra Analytics helps ensure renewables projects are built on-time and on-budget. We are looking for an operations research data scientist to help us solve the most impactful supply chain problems in renewable energy. In this cross-functional role you will leverage your experience in mathematical optimization and monte carlo simulation to build software tools that optimize inventory and reduce operational risk.
Key Responsibilities:
- Build simulation and optimization models to solve constantly evolving supply chain problems
- Develop decision-support tools that impact supply chain strategy in partnership with software engineers and data engineers
- Collaborate with stakeholders throughout the organization to improve operational efficiency and profitability
- Help support and maintain existing models and tools owned by the team
- Assist with data-pipelining in preparation for modeling
Skills:
- Mathematical Optimization: Mixed integer programming, linear programming
- Monte Carlo Simulation
Software Skills:
- R and/or Python
- One or more optimization algebraic modeling languages (e.g., Pyomo or AMPL)
- One or more optimization solvers (e.g., Gurobi, CBC, CPLEX, Xpress, GAMS)
Ideal Experience:
- 1-3 years of industry experience building mixed integer programming models and monte carlo simulations
Credentials:
- BA / BS in a STEM field – operations research, industrial engineering, or management science preferred
- Master’s degree in the above is not required
Job Overview
This position is responsible for developing algorithms, modeling techniques, and optimization methods that support many aspects of NextEra and FPL business. Employees in this role use knowledge of machine learning, optimization, statistics, and applied mathematics along with abilities in software engineering with a focus on distributed computing and data storage infrastructure (i.e., “Big Data”).
Job Duties & Responsibilities
- Develops machine learning, optimization and other modeling solutions
- Prepares comprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses
- Works with big data and distributed computing platforms
- Develops software and contributes to product development
- Performs other job-related duties as assigned
Required Qualifications
- Bachelor's Degree
- Experience: 0+ years
Preferred Qualifications
- Master's Degree
NextEra Energy offers a wide range of benefits to support our employees and their eligible family members.
Employee Group: Exempt
Employee Type: Full Time
Job Category: Science, Research, and Technology
Organization: NextEra Energy Project Management, LLC
Relocation Provided: Yes, if applicable
NextEra Energy is an Equal Opportunity Employer. Qualified applicants are considered for employment without regard to race, color, age, national origin, religion, marital status, sex, sexual orientation, gender identity, gender expression, genetics, disability, protected veteran status or any other basis prohibited by law.
NextEra Energy provides reasonable accommodation in its application and selection process for qualified individuals, including accommodations related to compliance with conditional job offer requirements, consistent with federal, state, and local laws. Supporting medical or religious documentation will be required where applicable and permitted by applicable law. To request a reasonable accommodation, please send an e-mail to [email protected], providing your name, telephone number and the best time for us to reach you.
NextEra Energy will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.
NextEra Energy does not accept any unsolicited resumes or referrals from any third-party recruiting firms or agencies.
Nearest Major Market: Palm Beach
Nearest Secondary Market: Miami
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 9,653 AI roles we're tracking, Research Scientist positions make up 2% of the market. At NextEra Energy, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,408.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
NextEra Energy AI Hiring
NextEra Energy has 1 open AI role right now. They're hiring across Research Scientist. Based in Juno Beach, FL, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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