Why pre-screen renewable energy economists before the interview
A single cost figure per unit of energy is the most quoted and least useful number in this sector. It hides when the power arrives, what the grid costs to accommodate it, and what happens when a support scheme changes. Economists worth hiring model those explicitly and can say where a past forecast was wrong. A short screen asks exactly that.
What actually matters when screening Renewable Energy Economist candidates
- 01
Technical command
Check command of LCOE and levelised storage cost builds, discount rate selection, capacity factor assumptions, merchant curve forecasting, and tools such as PLEXOS, Aurora, HOMER or Python dispatch models.
- 02
Deals and deliverables that closed
Probe specific deliverables: PPA price floors, subsidy auction bids (CfD, ITC/PTC transfer), grid connection business cases, or curtailment risk studies that informed a real investment decision.
- 03
Risk judgement
Test how they treat merchant price risk, negative pricing hours, basis risk, policy reversal, and interconnection queue delay; ask where their forecast was wrong and why.
- 04
Explaining it to decision-makers
Assess how they brief investment committees, regulators or non-technical developers: charts used, memo structure, defending a capture rate assumption under challenge from commercial teams.
Pre-screening questions to ask Renewable Energy Economist candidates
12 questions grouped by what they test. Ask the same set in every screen and score answers on a consistent scale, or send them as an async video screen and compare answers side by side.
Analysis that decided
3 questions01Can you discuss a time when your analysis changed a renewable energy strategy?
Listen forA decision that changed with the analysis behind it, and the person who acted on it named.
Analysis described without a decision, or influence claimed with no specific outcome.
02Describe a project where you used economic modelling to support a decision.
Listen forA model they built with assumptions documented, and sensitivity run on the ones that matter.
Models inherited and not understood, or key assumptions never tested for sensitivity.
03Can you give an example of influencing policy or investment decisions?
Listen forWork that reached decision makers, with the recommendation and the outcome both stated.
Reports published without follow-up, or influence assumed from the audience reached.
Models the whole system
4 questions04How do you evaluate the financial viability of a renewable project?
Listen forRevenue certainty, capture price and grid costs modelled rather than a single cost figure.
Viability judged on levelised cost, or curtailment and connection costs left out.
05What methods do you use to forecast energy prices and demand?
Listen forScenario ranges rather than point forecasts, with the drivers of uncertainty identified explicitly.
Single price paths used for investment decisions, or forecast error never reviewed.
06Have you conducted a cost-benefit analysis for an energy project?
Listen forDiscount rate justified and tested, with external costs and benefits treated transparently.
Discount rate chosen without justification, or benefits included that cannot be evidenced.
07Which economic tools or software do you use for this analysis?
Listen forModels built in tools that others can audit, with version control and documented inputs.
Spreadsheets nobody else can follow, or model versions that cannot be reconciled.
Policy risk modelled
3 questions08What role do government incentives play in your evaluations?
Listen forSupport schemes modelled with their expiry and change risk explicitly tested in scenarios.
Incentives assumed permanent, or project viability dependent on subsidy without a sensitivity.
09Can you explain your familiarity with energy policy and its economic effects?
Listen forMarket design and support mechanisms understood in the markets they have worked in.
Policy described generally, or mechanisms confused between different jurisdictions.
10What is your experience with carbon pricing and its effect on project economics?
Listen forCarbon price paths modelled as uncertain, with the effect on relative technology costs quantified.
A single carbon price assumed indefinitely, or its effect on competitiveness not modelled.
Findings land
2 questions11How do you handle uncertainty and risk in renewable energy investments?
Listen forRanges and probabilities presented rather than point estimates, with downside cases run.
Central cases presented alone, or uncertainty removed before the results are circulated.
12How do you communicate complex economic findings to non-economists?
Listen forFindings expressed as decisions and trade-offs, with the uncertainty preserved in the summary.
Results simplified into a single number, or caveats dropped from executive summaries.
How to score responses
Score every candidate on the same four criteria immediately after the screen. At this stage you are shortlisting for panel interviews, not making the final call.
Technical command
35%5Explains WACC and degradation assumptions behind their own LCOE builds and names the dispatch or price forecasting model they maintained.
Deals and deliverables that closed
25%5Cites named projects with MW scale, the pricing or bid they modelled, and what the developer, regulator or investor decided as a result.
Risk judgement
25%5Quantifies downside scenarios with sensitivity ranges, flags assumption fragility unprompted, and describes a forecast miss with the correction made.
Explaining it to decision-makers
15%5Translates dispatch and capture price modelling into a clear investment recommendation, holding the line on evidence when pushed for a friendlier number.
Levelised cost hides when the power arrives and what the grid costs. A one-way video screen asks what the model missed.
Try it on HirevireScreening FAQ
Process basics
How long should a pre-screening round for this role take?
Fifteen minutes across eight to ten questions, answered async. Enough to establish analysis that changed decisions, test their modelling method, and check policy risk and communication.
How much market-specific knowledge matters?
Considerably. Market design, support schemes and grid charging differ by country and shape project economics more than technology cost does, so check where they have worked.
Evaluating answers
What is the strongest signal when screening this role?
A forecast that turned out wrong. Economists who check their work know which assumption failed. Anyone whose models always held has not compared them against what actually happened.
How do I judge their modelling depth?
Ask how they treat intermittency. Real answers cover capture prices and system integration costs. Anyone whose analysis stops at levelised cost is comparing technologies that are not comparable.
Go deeper on this role
Sanat has been hiring since 2012 and watching the recruitment industry change up close ever since, and turned that screening process into Hirevire's video screening platform. LinkedIn
