This question evaluates quantitative financial modeling, scenario analysis, and decision-making skills for a Data Scientist role by requiring calculation of annual profit and payback periods, incorporation of carbon credits, and comparative output analysis; it tests the Statistics & Math domain and emphasizes practical application of numerical analysis rather than purely conceptual theory. It is commonly asked to gauge proficiency in applying statistical and mathematical techniques to real-world energy investment problems, performing sensitivity and scenario analyses, and integrating non-financial considerations such as supply risk, permitting complexity, and scalability into evidence-based comparisons.

Compare two investments. Assume all energy prices/costs are per MWh and the selling price is 12.5M; variable cost = 2.5M; variable cost = 5 per MWh applies to both projects, recompute paybacks; (3) what annual output would the biomass plant need to match the solar project’s payback from (1)? (4) make a recommendation between A and B, citing at least three non-financial considerations (e.g., fuel supply risk, permitting/interconnection, scalability, offtake certainty).