Data Analyst - Forecasting and Optimization
- Full-time
Company Description
Customized Energy Solutions (CES) is a global energy services and technology company that helps market participants operate, comply, and compete in deregulated electricity and natural gas markets. Founded in 1998 and headquartered in Philadelphia, CES works with utilities, independent power producers, energy suppliers, developers, asset owners, and investors across North America and globally.
CES delivers market intelligence, regulatory and market design support, asset and portfolio management, retail market operations, and energy technology solutions. Our teams track and interpret ISO/RTO rules and policy developments, support resource planning and market participation, manage operational and settlement processes, and develop proprietary software platforms—including CES BLUE, GOLD, RED, GRIDBOOST, and CoMETS—that help clients manage risk, optimize performance, and respond effectively to market change.
CES is committed to advancing transparent, efficient, and non-discriminatory energy markets while delivering practical, high-quality solutions marked by integrity, rigor, and long-term client value.
CES has been nationally and regionally recognized for sustained growth and innovation, including listings on the Inc. 500|5000 and Philadelphia Business Journal’s Top 100 Companies, as well as a Best Places to Work designation with Hall of Fame status for five or more consecutive years.
With headquarters in Philadelphia and offices across the U.S., Canada, Japan, India, and Vietnam, CES offers a collaborative, flexible, and globally connected work environment for professionals passionate about the future of energy.
Job Description
CES GridBOOST is an advanced energy management platform that enables grid assets to participate intelligently in electricity markets. As a Data Analyst in the Forecasting and Optimization team, you will sit at the core of the product — owning the quantitative models that determine how GridBOOST bids into day-ahead, intraday, and ancillary service markets. Your work will span two tightly coupled disciplines: building optimization engines that translate market rules and grid constraints into optimal bid strategies and developing machine learning models that forecast electricity prices to inform those strategies. You will work in a cross-functional team alongside software engineers and market operations specialists, with your models running in production and directly influencing real-world market outcomes.
Position Responsibilities
- Design and implement optimization models to optimize energy bids across day-ahead and real-time electricity markets
- Translate electricity market rules, operational constraints, and grid conditions into mathematical formulations for the GridBOOST bid optimization engine
- Build and maintain machine learning pipelines for short-term electricity price forecasting, covering day-ahead, intraday, and ancillary service markets
- Engineer features from weather, demand, generation mix, and historical market signals to improve forecast accuracy
- Collaborate with software engineers to integrate models into production systems connected to real-time market data feeds
- Monitor live model performance, conduct systematic backtesting, and iterate on bid strategies and forecast models based on observed outcomes
- Analyse post-dispatch results and produce clear, actionable insights for trading and grid operations teams
- Track changes in regulatory frameworks, market mechanisms, and grid infrastructure that may affect model assumptions or bid strategies
- Document model logic, assumptions, and limitations to support auditability and knowledge transfer
Qualifications
- Bachelor's or Master's degree in Operations Research, Applied Mathematics, Electrical Engineering, Data Science, or equivalent
- 3+ years of hands-on experience in the electricity domain — energy trading, grid operations, market analysis, or a closely related quantitative role.
- Demonstrated experience formulating and solving optimization problems for real-world scheduling, dispatch, or resource allocation use cases
- Proficiency with at least one solver (Gurobi, HiGHS) and an optimization modelling library (Pyomo or similar)
- Hands-on experience building and deploying ML forecasting models for time-series data, preferably electricity prices or energy load
- Strong Python skills including pandas, scikit-learn, and at least one deep learning frameworks
- Experience working with high-frequency time-series market data and external data APIs
- SQL proficiency for querying and extracting market and operational data
- Ability to communicate complex quantitative results clearly to non-technical stakeholders
Preferred
- Solid understanding of U.S. ISO/RTO electricity markets, including their clearing mechanisms and pricing rules (Highly Preferred)
- Hands-on experience building and deploying forecasting and bid optimization algorithms in the electricity markets
- Ability to work with a remote and global teams across multiple time zones
Additional Information
CES offers a competitive salary commensurate with experience, plus a performance bonus, profit-sharing, a Medical Savings Account, comprehensive health insurance, disability and life insurance, 401(k) matching, and tuition reimbursement.
Beyond the package, here’s what you can expect at CES:
- Meaningful responsibility and the opportunity to make a real impact in dynamic energy markets.
- The chance to learn from and collaborate with experienced professionals across global teams.
- Ongoing opportunities to strengthen your technical, analytical, and leadership skills.
- A supportive culture that values initiative, accountability, and continuous professional growth.
Customized Energy Solutions provides equal employment opportunities to all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy apply