**REMOTE POSITION** Position Summary The Manager, Commercial Analytics, BESS Modeler owns quantitative revenue modeling and technoeconomic optimization analyses for standalone battery energy storage, solar, and hybrid solar plus storage assets across major U.S. power markets. This role supports asset monetization activities including M&A, origination, and other commercial transactions by translating market rules, fundamentals, and customer and contract structures into defensible revenue forecasts and valuation inputs. The role partners with Development, Engineering, Transmission, Finance, Operations, and Commercial teams to deliver timely, decision ready analytics and clear recommendations. Role Requirements Education: Bachelor’s degree in economics, finance, engineering, or a related field; advanced degree or certification preferred. Years of Experience: 5 to 7 years of energy revenue modeling experience in an energy development company, IPP, or consulting firm, including direct experience with storage and or hybrid asset modeling. Additional Skills, abilities & knowledge: - Demonstrated ability to model Vesper’s values, Accountability, Respect, Courage, Collaboration, and Continuous Improvement, through day to day behaviors (e.g., flags risks early, communicates directly, involves the right stakeholders early, and documents and shares learnings). - Demonstrated expertise in revenue modeling for solar, storage, and hybrid solar plus storage assets, including storage revenue stacking and optimization strategies. - Strong understanding of ISO and RTO market operations and rules governing energy storage participation across products including energy, ancillary services, and capacity (as applicable). - Strong understanding of power market fundamentals, including supply and demand dynamics, fuel price sensitivity, and transmission constraints, and ability to incorporate these drivers into analytical models. - Proficiency in Python and SQL for analytics and model development, including experience with common libraries such as pandas, NumPy, SciPy, and data visualization tools such as Matplotlib or Plotly. - Strong quantitative and statistical skills, including time series manipulation and the ability to synthesize large datasets into actionable insights. - Working knowledge of linear programming and mixed integer programming concepts; familiarity with optimization frameworks and solvers such as Pyomo, CVXPY, or Gurobi preferred. - Ability to explain complex modeling outputs and commercial structures clearly to internal stakeholders and external counterparties, including customers. - Strong organization and prioritization skills, able to manage multiple concurrent deliverables with high standards for accuracy, documentation quality, and on time execution. - Familiarity with offtake structures and key revenue contract concepts, including PPAs, tolls, build own transfer, and other long term structured revenue arrangements. Key Responsibilities - Own the development, maintenance, and continuous improvement of quantitative revenue and technoeconomic optimization models for standalone and co located storage, solar, and hybrid assets across major U.S. markets. - Deliver scenario analyses and revenue forecasts to support commercial decision making for asset monetization activities, including M&A diligence, origination pursuits, and structured transaction opportunities. - Optimize the storage revenue stack across applicable market products, ensuring alignment with ISO and RTO participation rules and translating constraints into defensible modeling assumptions. - Analyze market fundamentals, price forecasts, and regulatory dynamics and translate insights into clear implications for offtake strategy, asset valuation, and transaction structuring. - Interpret and incorporate production cost modeling and capacity expansion modeling outputs into deal level revenue views, sensitivities, and narrative explanations for internal approval. - Partner with Structured Finance and Finance teams to integrate revenue modeling outputs into project financial models and valuation work, ensuring traceability and consistent definitions. - Support proposal development and tracking by producing customer ready analytics, drafting quantitative content, and coordinating inputs, timelines, and responses with internal stakeholders. - Build repeatable tools, documentation, and standards for model governance, including version control practices, input assumptions, validation checks, and clear handoffs for cross functional use. - Communicate complex results to technical and non technical audiences, including explaining structures, trade offs, and key drivers to customers and internal executives. - Identify data gaps, workflow bottlenecks, and quality issues and implement improvements that increase speed, rigor, and consistency of commercial analytics deliverables.