Compare solar vs biomass paybacks and recommend

Quick Overview

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 solar vs biomass paybacks and recommend

Company: Capital One

Role: Data Scientist

Category: Statistics & Math

Difficulty: medium

Interview Round: Technical Screen

Compare two investments. Assume all energy prices/costs are per MWh and the selling price is $40 per MWh. Project A (Solar): initial investment = $12.5M; variable cost = $0; production profile = 75% of the year at 150,000 kWh/day and 25% of the year at 50,000 kWh/day. Project B (Corn biomass): initial investment = $2.5M; variable cost = $30 per MWh; steady output = 100,000 MWh per year. Tasks: (1) compute each project’s annual profit and payback period (profit used to offset the initial investment); (2) if a carbon credit of $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).

Quick Answer: 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.

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Oct 13, 2025, 9:49 PM
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Compare two investments. Assume all energy prices/costs are per MWh and the selling price is 40perMWh.ProjectA(Solar):initialinvestment=40 per MWh. Project A (Solar): initial investment = 12.5M; variable cost = 0;productionprofile=750; production profile = 75% of the year at 150,000 kWh/day and 25% of the year at 50,000 kWh/day. Project B (Corn biomass): initial investment = 2.5M; variable cost = 30perMWh;steadyoutput=100,000MWhperyear.Tasks:(1)computeeachproject’sannualprofitandpaybackperiod(profitusedtooffsettheinitialinvestment);(2)ifacarboncreditof30 per MWh; steady output = 100,000 MWh per year. Tasks: (1) compute each project’s annual profit and payback period (profit used to offset the initial investment); (2) if a carbon credit of 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).

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