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Principal Data Scientist

NextEra Energy

Juno Beach, FL, US, 33408Principal
Sign in to applyVerified 1h ago
Location
Juno Beach, FL, US, 33408
Work model
On-Site
Level
Principal

Skills

Machine LearningPythonSQL

About this role

Requisition ID:   96608    NextEra Energy Marketing is one of the nation’s leading electricity and natural gas marketers, and a key player in the energy markets in the United States and Canada. As a part of NextEra Energy Resources, we specialize in innovative energy strategies that maximize market value for our customers and stakeholders. Our team is skilled in market analysis, trading, risk management and delivering tailored customer solutions across North America. If you are a strategic thinker eager to make a significant impact in the fast-paced energy industry, join our team today.   Position Specific Description Position Specific Description   This Director role combines deep technical expertise with strategic leadership. You will set the vision for grid modeling and congestion analytics, ensure analytical rigor at scale, and translate complex power system and market dynamics into actionable commercial and risk management decisions. In addition to owning the technical roadmap, you will partner closely with traders and other senior stakeholders. Key Responsibilities Technical Ownership & Delivery

Own and advance detailed  DC/AC power flow and contingency models  for PJM, ERCOT, and other ISO/RTOs. Model and forecast  flowgates, interface constraints, thermal and voltage limits  impacting DA/RT markets and FTR/CRR/ARR outcomes. Build, calibrate, validate, and back-test  market simulation engines  that replicate ISO dispatch, pricing (LMP, congestion, losses), and auction mechanics. Monitor and model  transmission topology changes , outages, new project interconnections, and load growth trends. Translate  ISO tariffs, FERC regulations, and market rule changes  into modeling assumptions and logic. Design and govern  automated, production-grade data pipelines  integrating grid, market, weather, and asset data into trading, risk, and settlement systems.

Strategy, Vision & Business Impact

Define the  multi‑year strategy and roadmap  for grid modeling and congestion analytics aligned with NextEra’s trading, development, and risk objectives. Quantify and communicate  congestion risk, nodal margin drivers, sensitivities, and scenario outcomes  to trading desks and executive leadership. Partner with development, origination, and asset optimization teams to support  build/no‑build decisions, merchant valuations, and hedging strategies . Identify and incubate  new analytical capabilities  (advanced optimization, ML/AI, cloud-native architectures) and drive them from POC to production.

Required Qualifications

Bachelor’s degree (Master’s or PhD preferred) in Electrical Engineering, Power Systems, Applied Math, Physics, Computer Science, or related field. 7+ years  of progressive experience in ISO/RTO market modeling, congestion analytics, or power systems analysis. Deep expertise in  DC/AC power flow, contingency analysis, FTR/CRR/ARR markets, and settlement mechanics . Proficiency with industry tools (e.g., PSS/E, PowerWorld, Dayzer, Enelytix/TARA, Enverus Mosaic/Panorama, YES Energy or similar) and strong programming skills (Python, SQL, etc.). Demonstrated ability to lead teams, influence senior stakeholders, and translate analytics into business decisions.

Preferred Qualifications

Operational experience in PJM and/or ERCOT markets. Experience collaborating with congestion trade desks. Job Overview

This position is responsible for leading the development of 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

Provide thought leadership, set technical strategy, and identify possible uses of data science