Sr Data Scientist - Energy Supply
Tampa Electric
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Benefits offered by this job
Job summary
Tampa Electric is seeking a Senior Data Scientist - Energy Supply to lead analytics for generation performance, leveraging statistics, machine learning and domain knowledge. You will develop data pipelines for PI, GADS, GPIF, PGS data, and create fleet-level insights to guide maintenance, reliability and capital planning.
You will collaborate with Asset Management to identify risks, build predictive models, and deliver actionable insights, while mentoring teams and guiding data strategy across
Qualifications
- 7 years of progressive work experience in data science, analytics, machine learning engineering, with at least 2 years in the utility or energy sector.
- Bachelor’s degree in Engineering, Data Science, Applied Mathematics or Statistics is required.
- Advanced degree in data science or related fields is preferred.
- Strong knowledge of analytics, IT/OT systems, and ability to translate technical results for non-technical stakeholders.
Responsibilities
- Lead development, implementation and operation of analytics to monitor generation performance using advanced statistics and ML.
- Collaborate with Asset Management to prioritize maintenance and measure impact of maintenance and operations.
- Develop data pipelines and architectures to store and process large-scale data (PI, GADS, GPIF, PGS, etc.).
- Create fleet-level analytics on Power BI for performance comparison and operational review.
Skills
Education
Tools
Job description
The Sr Data Scientist - Energy Supply plays a critical role in achieving our safety, reliability, resilience and modernization goals for our generating assets. Develops and applies advanced analytics, statistics, machine learning and domain-specific knowledge to transform complex data (PI Data, WorkMan, GADS, GPIF, PGS Data) into actionable insights. Coordinates closely with the Manager, Asset Management to develop methods to utilize the data available to identify performance risks and develop predictive methods to mitigated equipment, system and operational failures Develops the vision for generation analytics to provide comprehensive performance insights which bridge data, operations, maintenance, engineering.
- Lead the development, implementation and operation of Analytics to monitor generation performance. Analytics will include the development and application of statistical and machine learning to detect, track and predict functional equipment and system failures of the generating assets such as: Anomaly Detection utilizing multivariate statistical models and unsupervised learning algorithms, Time Series Analysis and Forecasting, Failure Mode Prediction utilizing classification models, Survival Analysis to estimate time to failure, Event Detection and Classification, Asset and system degradation modeling, causal inference to link asset failure with contributing factors, Statistical Process Control and others. (20%)
- Lead the development of analytics using Asset Management and formal reliability engineering to achieve safety, compliance, reliability, performance, affordability and resilience goals for the generating fleet. These analytics support the prioritization of maintenance of the generating assets and measurement of the impact of maintenance, track prioritized backlog of maintenance, capital improvement and operational improvements for stakeholders. (20%)
- Lead the vision for analytics at the generating fleet level collaborating closely with Technology (information and operational technology) department to develop data pipelines and architectures that support the acquisition, storage, and processing of large-scale data (e.g., PI, Canary, Workman, GADS, GPIF, PGS Gas Data, Gridmax). This includes the acquisition of asset condition from inspections, reports, and performance data and the application of Analytics on this data to inform work and operational changes. (20%)
- Lead development of fleet level analytics centrally located on Power BI to compare performance and review operations at a fleet level. This includes coordination with Data Analytics Platform to coordinate data. (10%)
- Lead development of analytics for the support of performance reporting up to and including Net Generation Reporting, outage reporting and planning. (10%)
- Guide and oversee the data strategy, and Data Analytics Platform access to provide agentic and semantic tools to the engineering teams. The AI tools should allow the engineering teams at the generating assets to improve performance, reliability, maintenance planning, and long-term capital planning. (10%)
- Mentor others and foster a collaborative environment focused on innovation and technical rigor. (10%)
Indirect: May have indirect supervision of project and System governance teams.
Key Internal: Asset Management, Generating Assets, Regulatory, OPMECC, (VP, directors, managers and program leads). Works with IT business relationship manager to prioritize a system portfolio roadmap and coordinate execution of the projects. IT and ES technical leads to develop and implement an effective technology plan.
Key External: Consultants (Solution implementers, etc.), Contractors, Industry Associations, Vendors
Required: Bachelor’s degree in Engineering, Data Science, Applied Mathematics or Statistics.
Preferred: Advanced degree (Master’s or PhD) in data science, statistics, engineering and/or information systems representing a blend of data science and ability to apply data science to understand electric grid performance. Graduate course work in Machine Learning/AI, predictive modeling, time-series forecasting, power system reliability or risk analysis.
Preferred: Certified Analytics Professional, Python for Data Science, Reliability related certification, etc.
Required: 7 years of progressive work experience in data science, analytics, machine learning engineering, with at least 2 years in the utility, energy or related sector.
Preferred: Electric utility engineering and operational, asset experience with experience applying data science, analytics with interdisciplinary team of engineers, field operators and Information Technology teams.
Required: Broad knowledge and skills in Analytics and IT/OT system solutions (see preferred below) and a problem-solving mindset with a focus on actionable outcomes. The ability to explain technical findings to non-technical stakeholders and collaborate across operations, engineering and regulatory teams.
Preferred: Programming & Development: Python, SQL, JavaScript, HTML/CSS, APIs, CLI, and Automation. Data Engineering: ETL/ELT, data modeling, large dataset processing, API and enterprise system integration, SQL Server, Snowflake, Azure, and cloud data platforms. Analytics & Machine Learning: machine learning, computer vision, statistical and predictive analytics, object detection, image segmentation, anomaly detection, and time-series analysis. Visualization & Geospatial: Power BI, DAX, Power Query, Power Automate, Esri GIS, geospatial analysis, interactive mapping, drone/aerial imagery analytics, executive dashboards, and real-time operational visualization. Software Solutions: full-stack application development, system integration, testing, debugging, and documentation.
Knowledge of statistical models (e.g., regression, time series forecasting, survival analysis, Bayesian methods) to detect patterns, estimate probabilities of failure, and quantify uncertainty in grid performance. Development of digital twins and grid simulations, using statistical models to calibrate, validate, and interpret electric grid behavior. Ability to apply hypothesis testing, anomaly detection, and probabilistic risk assessment techniques to evaluate system behavior and identify emerging reliability threats.
Ability and strong knowledge of machine learning models (e.g., random forests, neural networks, gradient boosting) that complement statistical analysis for high-dimensional, multi-source grid data such as 3D LiDAR point cloud data and imagery.
Ability to lead the design of model validation frameworks, ensuring robust, interpretable, and auditable outputs for operational decision-making.
- Puts Safety First – Protect people and the environment every day
- Be Curious & Adapt – Welcome change and keep learning
- Create Value for Customers – Build relationships and deliver quality work
- Be Accountable & Respectful – Do what’s right and follow through
- Foster Strong Teams – Build trust through teamwork and help people grow
Normal office environment. Occasionally required to work in an industrial environment. Travel within the Tampa Electric Service Area.
- Competitive Salary
- 401k Savings plan w/ company matching
- Pension plan
- Paid time off
- Paid Holiday time
- Medical, Prescription Drug, & Dental Coverage
- Tuition Assistance Program
- Employee Assistance Program
- Wellness Programs
- On-site Fitness Centers
- Bonus Plan and more!
TECO Energy and its companies serve a role in providing critical services to our community during an emergency. Team members are required to participate in the response/recovery activities related to emergencies/disasters to maintain service to our TECO Energy customers. Team members are required to work in their normal job duties or other assigned activities. Proper compensation will be made in accordance with the company's rules and procedures.
TECO Energy is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law, except where physical or mental abilities are a bona fide occupational requirement and the individual is unable to perform the essential functions of the position with reasonable accommodations.
In order to provide equal employment and advancement opportunities for all individuals, employment decisions at TECO Energy will be based on skills, knowledge, qualifications and abilities.
The contractor 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. 41 CFR 60-1.35(c)
It is the policy of TECO Energy to provide reasonable accommodation for all qualified disabled individuals who are employees and applicants for employment, unless it would cause undue hardship. The corporation will adhere to applicable federal and state laws, regulations and guidelines, including, but not limited to the Americans with Disabilities Act (ADA) of 1990 and section 503 and 504 of the Rehabilitation Act of 1970s.
Applicants may request reasonable accommodation in the application process five business days prior to the time accommodation is needed.
Pre-employment physical exams may be required for positions with bona fide job-related physical requirements regardless of disability.
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