Sr. Energy Analytics Analyst

Hanwha Energy USA•Houston, TX

5h•$115,000 - $140,000•Onsite

About The Position

Hanwha Energy USA is seeking an experienced, analytical, detail-oriented Sr. Energy Analytics Analyst to support commercial, trading, risk management, and operational decisions through data analysis and forecasting. The role calls for 1–3 years of experience in deregulated retail electricity and/or wholesale power markets, with knowledge of ERCOT and PJM market fundamentals, load forecasting, price formation, risk management, and supply portfolio optimization. As a member of the Energy Analytics team, the analyst will develop and maintain analytical models, derive insights from large datasets, and work with stakeholders across trading, origination, risk, supply management, and retail businesses. The position combines technical capabilities in SQL, Python, data visualization, and AI/LLM technologies with practical energy-market knowledge. The analyst will take ownership of projects from concept through implementation, work independently with minimal supervision, and communicate with technical and business audiences. The role reports to the Sr. Director of Energy Analytics. It is based onsite at the Houston, Texas office, and candidates should be within commuting distance.

Requirements

Bachelor’s degree in Finance, Economics, or another quantitative hard science.
1–3 years of energy industry experience applying modelling techniques in successful business applications.
Strong understanding of ERCOT market structure and fundamentals; familiarity with PJM markets is preferred.
Hands-on experience supporting retail power and/or wholesale power businesses through load forecasting, price forecasting, market analytics, risk management, and supply portfolio optimization initiatives.
Strong knowledge of Python, SQL, and visualization tools such as Plotly and Power BI.
Strong analytical and statistical problem-solving skills.
Strong interpersonal, verbal, written, and presentation skills, including the ability to collaborate with technical and non-technical teams.
Ability to multitask, manage multiple deadlines, prioritize tasks, and work in a fast-paced, dynamic environment.
Demonstrated ability to independently manage projects from inception through successful implementation.
Self-motivated, collaborative, and able to work independently; demonstrates initiative, accountability, and attention to detail.
Eligible to work in the USA for any employer without sponsorship.

Nice To Haves

Strong technical knowledge of time-series modelling, including GBM and LSTM, and deep learning or generative AI methods, including CNN, VAE, and GAN.
Thorough understanding of energy-industry analytical drivers, including weather, consumption patterns, and wholesale and retail prices, particularly in ERCOT and PJM.
Experience with ETRM systems, Dayzer, Yes Energy, Hitachi/Endur, Amperon, or similar energy-market platforms.
Working knowledge of generative AI, large language models (LLMs), AI-assisted development tools, and practical business applications of AI.
Experience developing AI-enabled analytics solutions, agents, copilots, or workflow automation tools.
Knowledge of renewable generation, battery storage, natural gas markets, and power asset optimization.
Advanced degree, preferably a Ph.D. in Engineering, Math, Physics, or a related field.

Responsibilities

Develop and enhance analytical solutions for wholesale power, retail energy, risk management, and supply optimization.
Build, maintain, and improve load, price, growth margin forecasting, and market intelligence models for ERCOT and PJM markets.
Support trading, risk, supply management, and marketing teams through scenario analysis, position evaluation, exposure reporting, pricing support, and market research.
Design and develop scalable data pipelines, datasets, and analytics tools using SQL and Python.
Use generative AI, large language models (LLMs), and machine learning techniques to improve business efficiency, automate workflows, and enhance forecasting capabilities.
Create dashboards, reports, and visualizations to support stakeholder decision-making.
Partner with technology, commercial, risk, and operations teams to translate business requirements into analytical solutions.
Lead analytics projects from requirements gathering through development, testing, deployment, and ongoing support.
Communicate analytical findings and recommendations to technical and non-technical stakeholders.
Identify opportunities to improve processes, data quality, forecasting methodologies, and business workflows.
Perform ad hoc analysis and assist with critical business needs as required.