Job Title & Compensation
Lead Data Analyst – Commodities & Energy Trading (Front Office) – London, Hybrid – up to £115k + Bonus.
Responsibilities
- Innovative Model Development: Lead the creation and enhancement of PLEXOS energy market models, integrating industry best practices and staying ahead of evolving modeling techniques to maintain a competitive edge.
- Collaborative Calibration and Forecasting: Work closely with the data team to calibrate datasets and integrate forecast data for high‑quality PLEXOS model outputs; collaborate with the technical team to incorporate additional data sources, improving model accuracy.
- Cross‑Team Coordination: Drive initiatives across the Indian Data Centre, technical, and product teams, ensuring effective collaboration to improve data quality and refine modeling methodologies.
- Analytical Reporting: Produce insightful reports that translate complex modeling results into actionable insights, supporting informed decision‑making.
- Comprehensive Market Analysis: Conduct detailed reviews of energy markets, gathering and curating data to shape energy models for in-depth analysis.
- Analytical Proficiency: Strong ability to analyze complex models and identify patterns within intricate data.
- Proactive Problem Solving: Anticipate challenges and address them efficiently with a proactive approach.
- Excel Mastery: Advanced proficiency in Excel for data analysis and manipulation (programming skills not required).
- Database Expertise: Knowledge of database management for seamless integration of diverse datasets.
- Energy Market Forecasting: Expertise in forecasting and modeling energy markets with a deep understanding of market dynamics.
- Multilingual Advantage: European language skills are a plus for effective communication within a diverse team.
- PLEXOS Modeling Experience: Proven experience with PLEXOS or similar modeling tools, showcasing deep expertise in simulation and production cost modeling.
- Meticulous Attention to Detail: Strong focus on accuracy and precision in modeling outcomes and reporting.
- Strong Communication Skills: Ability to simplify and communicate complex modeling results clearly and concisely.
- Adaptability to Client Needs: Flexible in adapting to evolving client requirements, delivering solutions that meet their needs effectively.
Qualifications
- Hold a Master’s Degree in Economics, Engineering, Mathematics, or Mathematical Science.
- Have experience in an analytical role, highlighting a proven track‑record of applying analytical skills to solve complex problems and generate valuable insights.
- Possess experience in electricity, gas, or fuels market analysis and/or forecasting, showcasing a nuanced understanding of market dynamics and the ability to predict future trends.
- Demonstrate a background in consulting or a client‑facing role, indicating an ability to engage with clients, understand their needs, and deliver solutions that align with their strategic objectives.
Company Overview
Energy Exemplar, founded in 1999 in Adelaide, Australia, is an award‑winning software portfolio encompassing the modelling and simulation platform PLEXOS, Aurora, and Adapt2. Trusted by innovative organisations worldwide, Energy Exemplar empowers stakeholders across the entire energy value chain to revolutionise the energy ecosystem and collaboratively plan for a sustainable future with unprecedented clarity, speed and innovation.
Awards & Recognition
- SaaS Company of the Year (2025) – Global Business Tech Awards.
- Environmental Impact Award (2025) – E+E Leaders Awards.
- IPPAI Power Awards (2025) – Winners.
- Platts Global Energy Awards (2024) – Finalist (Grid Edge).
- Reuters Global Energy Transition Awards (2024) – Finalist (Technologies of Change).
- ICON Awards – Top 50 Marketing Team (2024).
About the Position
The EMEA Data Team at Energy Exemplar focuses on developing comprehensive short‑ and long‑term energy market modelling datasets for European markets. This role involves detailed review of electricity markets, gathering and curating data into PLEXOS‑based models for analysis and forecasting. It requires close collaboration with global technical teams to calibrate, tune and enhance data quality and modelling methodologies, and a strong understanding of hydrogen and/or gas markets is highly beneficial.