Title: Sr. Data Scientist, Grid Analytics
Company : Tampa Electric Company
Location: Bearss Operations Center
State and City: Florida - Tampa
Shift: 8 Hr. X 5 Days
Hiring Manager: Patrick L Shell
Recruiter: Mark E Koener
TITLE: Sr Data Scientist - Grid Analytics
PERFORMANCE COACH: Director, Asset Management
COMPANY: Tampa Electric
DEPARTMENT: Asset Management
POSITION CONCEPT:
The Sr Data Scientist - Grid Analytics plays a critical role in achieving our safety, reliability, resilience and modernization goals for electric grid. Develops and applies advanced analytics, statistics, machine learning and domain-specific knowledge to transform complex utility data (smart meter, grid operational, geospatial and imagery) into actionable insights. Coordinates closely with the Manager, Asset Management Distribution to identify grid performance risks and advise on proactive mitigation of equipment, system and operational failures ensuring safety, compliance, reliability, performance, affordability and resilience of the electric grid. Develops the vision for grid analytics to provide comprehensive grid performance insights which bridge data engineering, operations, system planning, maintenance, engineering and other grid functions.
Primary Duties and Responsibilities:
SUPERVISION
Indirect Supervision: May have indirect supervision of project and System governance teams.
RELATIONSHIPS
Key Internal: Asset Management, AAOS, DEO, DCC, ECC, Substation, Transmission operations and engineering (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
QUALIFICATIONS
Education
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.
Licenses/Certifications
Preferred: Certified Analytics Professional, ESRI GIS Certification, Python for Data Science, Reliability related certification, etc.
Experience
Required: 7 years of progressive work experience data science, analytics, machine learning engineering, with at least 2 years in the utility, energy or related sector.
Preferred: Electric utility engineering and operational, distribution grid asset experience with experience applying data science, analytics with interdisciplinary team of engineers, field operators and Information Technology teams.
Knowledge/Skills/Abilities (KSA)
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. Theability to explain technical findings to non-technical stakeholders and collaborate across operations, engineering and regulatory teams.
Preferred: Knowledge of the following: Programming: Phyton, R, SQL. Tools/Platforms: Databricks, Azure, Snowflake. Data Handling: Extraction, Loading and Transformation (ETL), large dataset manipulation, cloud storage and processing, APIs. Visualization: Power BI, ESRI Geospatial Analysis
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.
WORKING CONDITIONS
TECO offers a competitive Benefits package!!
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!
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