Why YOU want this position At Enverus, we're committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world. We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we're helping our customers make better decisions that help provide communities around the world with clean, affordable energy. The energy industry is changing fast. But we've continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn't be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds. Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow. The role We publish long-term zonal power price forecasts across the North American ISOs. The team builds the view together: the load forecast, the capacity mix and build plan, retirements, fuel, and policy. This seat runs the production cost model that turns that view into hourly hub and zonal prices. How often we can refresh the forecast, and how many questions we can answer with it, depends on this role. You own the model and help shape the view. You work with the regional analysts on the load, build, and policy assumptions, run the model, validate the output, and explain what it did and why. When the model says something the team did not expect, you are the one who works out whether that is the market or the model. This is not a client-facing role. You will not be on sales calls or on stage at conferences. You will be in the room when the team forms its view, and your name goes on the research you help shape. At the Senior Analyst level you run the quarterly cycle without day-to-day supervision. You will have a handover period and Juan to escalate to, but the runs, the diagnostics, and the schedule are yours from the first full cycle. This role reports to Juan Arteaga, who leads Power Market Fundamentals & Long-Term Forecasting, within the broader Power & Renewables Intelligence group led by Ryan Luther. This role can be based in any of our North American offices or remote. You will not be in front of clients, but you will be working with our research analysts every single day, so you still need to be someone people want to work with. A day on the team Pick up the quarter's updated load forecast from the regional analyst, reconcile it against last quarter, and get it into model-ready shape before the run kicks off. Launch a full ERCOT run over coffee, then spend the afternoon working out why 2032 summer scarcity hours moved 40% against the last vintage, and which input did it. Turn around a scenario for an analyst who needs to know what six incremental gigawatts of data center load in PJM does to around-the-clock prices, and have it back to them by Friday. Work out with the West analyst whether this year's low WECC prices are a durable feature of the renewable build-out or a transitory one, and what the model needs to represent it. Backcast last year's forecast against what the market actually cleared and work out where the model missed and why. How we work Most research shops give ownership of the hardest problems to the most senior person on the team; everyone below executes. We do the opposite. Every analyst, even at entry-level, owns their projects end-to-end and pulls in senior team members for guidance. That hands-on, problem-by-problem ownership is how you build the confidence and judgment to add real value to our clients, and it's the single biggest reason people stay on this team. The modelling is yours in exactly that sense: not a queue of tickets someone else prioritizes for you. Who thrives in this role • You speak well. You can explain what the model did and why, in plain language, to a room that includes people who have never run one, and hold your ground when they push back. • You disagree well. When an assumption looks wrong to you, you make the case with evidence and work it through with the team until the view holds up. • You're deep where it counts and broad everywhere else. You will know this model better than anyone, and you're just as interested in the market it describes. The best modelers we have worked with can tell you roughly what a result should look like before they hit run. • You care more about whether the price is right than how elegant the setup is. You will inherit a model you did not build. The job is to understand it, calibrate it, and improve it, not to replace it with your favourite tool. • You ask for help early. You'd rather make ten phone calls and look slightly less smart than struggle alone for two weeks. • You understand that excellent and on time outperforms perfect and late. • You'd rather write a tight one-pager than a 40-slide deck. • You take the work seriously, not yourself. What you'll own • The model. The runs, the inputs, the calibration, and the documentation. When the model produces prices that do not make sense, finding out why is your problem, and when it gets better, that was you. • The quarterly cycle. Take the load forecasts and capacity mix build plans the research team produces, integrate them, run the full ISO set, validate the results, and deliver the hub and zonal price files on a published schedule. Every quarter, on time, without a fire drill. • Input integration. Turn the team's load, build, retirement, and fuel assumptions into model inputs, on time. • Scenario throughput. Run ad hoc scenarios for the research, product, and commercial teams with turnaround measured in days. • Validation and diagnostics. Build the checks that catch a bad run before anyone else sees it, and separate the two failure modes cleanly: the model did the wrong thing, which is yours to fix, or the assumption was wrong, which is yours to surface. • Explaining the mechanism. When a price view moves between vintages, you are the person who can say which mechanical driver moved it: which units set the margin, which hours, which input changed. Same day. • Continuity. Document the model well enough that it survives your vacation, and a different team two years from now. • Shaping the view. Work with the regional analysts to build the view: what the assumptions should be and what the model says about them. Co-author the research where your analysis drives the story. Must-haves • 1 to 6 years of hands-on power market modelling, at an IPP, utility, ISO/RTO, consultancy, trading desk, or research/data provider. • You communicate clearly and confidently, out loud and in writing. You can walk the team or leadership through why a forecast moved, take hard questions in real time, and leave them understanding the answer. • You have been the primary operator of a long-term power price or capacity expansion model in a production setting where other people depended on the output. Consuming someone else's forecast does not count. • You bring your own view on supply, demand, and price formation, and you can defend it or change it when the evidence says so. • You can calibrate a model to history and tell a real market signal from a model artifact. • You understand how a long-term zonal price is actually produced: unit dispatch, marginal units and heat rates, fuel and emissions curves, reserve margins and capacity accreditation, renewable shapes, and how zones trade with each other. • Judgment about when a number is wrong, and the instinct to chase it down rather than ship it. • You work well with people even though you are not in front of clients. You will take input from half a dozen analysts every cycle, and they need to want to bring you problems. • You hit deadlines you did not set. The quarterly cycle has a date on it and clients are waiting on the other side of it. Helpful, but not required • Hands-on experience with a commercial model: Aurora, PLEXOS, EnCompass, GridView, SERVM, Dayzer, or SAInt. • Nodal price modelling or power flow experience. • Python, SQL, or advanced Excel for handling inputs and outputs. • Detailed familiarity with the market design of one or more of ERCOT, PJM, MISO, CAISO, and SPP, or with WECC outside CAISO. • Exposure to data center and other large-load forecasting. • Graduate work in power systems, operations research, statistics, or economics. What success looks like in your first 12 months • You run your first quarterly cycle with handover support and the next ones on your own, all on schedule. • Scenario turnaround is measured in days, and the team stops rationing what it asks the model for. • You have backcast the model against recent market outcomes and can show the team where it tracks and where it does not. • Someone else on the team can run the model from your runbook. You are not a single point of failure. • When research or leadership asks why a price view changed, they get a specific mechanical answer the same day. • You have made at least one substantive improvement to the model's mechanics that the research team signs off on. About Enverus & this team Enverus is the leading energy SaaS company delivering highly technical insights and predictive/prescriptive analytics that empower customers to make decisions that increase profit. We are a strategic partner to more than 6,000 customers in 50 countries, delivering business-critical insights to the global energy industry through a state-of-the-art SaaS platform built on industry-leading data and analytics. Our Power & Renewables Intelligence team produces research for institutional investors, hyperscalers, IPP developers, utilities, and corporate strategy teams. If you want to shape how the North American grid gets built over the next decade, this is the place to be. Originally posted on Himalayas