Are you passionate about transforming complex data into actionable insights? NextEra Energy is seeking an Associate Data Scientist to join its innovative team in Florida. This is an exciting opportunity for professionals who enjoy working with advanced analytics, machine learning, and data-driven decision-making in a fast-paced energy industry environment. If you are looking to build your career with one of the leading clean energy companies in North America, this role offers competitive compensation, professional growth opportunities, and the chance to contribute to meaningful projects that shape the future of sustainable energy.
Job Overview
| Field | Details |
|---|---|
| Company Name | NextEra Energy |
| Role | Associate Data Scientist |
| Qualification | Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related field |
| Job Location | Palm Beach Gardens, Florida, United States |
| Salary | $95,000 – $130,000 per year |
| Work Type | Hybrid / On-site (based on business requirements) |
| Job Type | Full-Time |
| Job Level | Associate Level |
| Industry | Energy & Utilities |
Job Description
This role focuses on developing and deploying machine learning models and analytics solutions that drive reliability and performance across power generation fleets. The Associate Data Scientist will support predictive maintenance initiatives by building, validating, and improving algorithms that identify emerging equipment issues and enable proactive decision-making.
Key responsibilities include:
- Developing and tuning machine learning and statistical models to improve alert quality, reduce noise, and increase actionable findings
- Supporting model deployment and monitoring within enterprise platforms, ensuring performance, scalability, and data integrity
- Analyzing operational and sensor data to uncover trends, failure precursors, and optimization opportunities across fossil and renewable assets
- Collaborating closely with reliability engineers and cross-functional teams to translate business problems into analytical solutions
- Contributing to continuous improvement of modeling frameworks, feature engineering, and feedback loops to enhance model effectiveness over time
The role requires a solid foundation in data science (machine learning, statistics), combined with practical software engineering skills and the ability to work with large, complex datasets in a production environment.
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
Selection Process
- Application Submission
- Resume Screening
- Initial HR Interview
- Technical Assessment
- Hiring Manager Interview
- Final Interview Round
- Background Verification
- Offer Letter & Onboarding
How to Apply
- Visit the official NextEra Energy careers website.
- Search for the “Associate Data Scientist” position in Florida.
- Review the job description and eligibility requirements.
- Prepare and update your resume with relevant skills and experience.
- Complete the online application form.
- Upload your resume and any required supporting documents.
- Submit your application.
- Monitor your email and application portal for updates regarding the recruitment process.
