Sr. Data Scientist, Grid Analytics

Title:

Sr. Data Scientist, Grid Analytics

Company

: Tampa Electric Company

Location:

Bayside Station

State and City:

Florida - Tampa

Shift:

8 Hr. X 5 Days

Hiring Manager:

Lauren Zaluk

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

- Lead the development, implementation and operation of Analytics to monitor grid performance. Analytics will include the development and application of statistical and machine learning to detect, track and predict functional equipment and system failures in the distribution grid 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, Geospatial statistical analysis, Event Detection and Classification, Asset and system degradation modeling, causal inference to link asset failure with contributing factors, Statistical Process Control and others.

- Lead the development of analytics using Asset Management and formal reliability engineering to achieve safety, compliance, reliability, performance, affordability and resilience goals for the electric grid. These analytics support the prioritization of maintenance in distribution grid and measurement of the impact of maintenance, track prioritized backlog of grid maintenance, capital improvement and operational improvements for stakeholders.

- Lead the vision for analytics in the new Grid Diagnostic center 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 grid data (e.g., SCADA, AMI, LiDAR, thermography, weather). This includes the geospatial acquisition of asset condition from patrols, Remote Sensing, the collection, processing and the application of Analytics on this data to inform work and operational changes.

- Lead the development of the analytics functions for Distribution grid models. This includes coordination with other electric system modeling stakeholders (Planning, DCC, DEO and others) to represent (computer model) the design/expected performance of the electric grid. The Sensing function is the establishment of requirements and the development of Sensing systems to measure the performance of the grid. This includes the communication, networking, storage and Analytics required to visualize the performance of the electric grid.

- Lead development of analytics for the support of Storm operations. This is a multi-year, multi-department roadmap to develop an improved estimation of expected damage, tracking of actual damage and outages in the grid, optimization of restoration, tracking of resources supporting restoration.

- Help define and execute the diagnostic center’s data strategy, integrating statistical analysis and predictive modeling into grid reliability programs. Communicate and present to data science and utility operations teams, ensuring analytical outputs directly support operational objectives and reliability standards. Communicate findings and recommendations to grid owner/operators, senior leadership, regulatory stakeholders, aligning data-driven insights with business goals.

- Mentor others and foster a collaborative environment focused on innovation and technical rigor.

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

- Normal office environment. Occasionally required to work in an industrial environment. Travel within the Tampa Electric Service Area.

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!