AI Lead - Value and Economics

Diamondback Energy•Midland, TX

About The Position

The AI Lead – Value and Economics establishes the enterprise framework for evaluating, measuring, and maximizing the business value of Diamondback Energy’s Artificial Intelligence (AI) investments. Partnering with AI leaders, Finance, and business stakeholders, this role develops credible valuation approaches, defines success measures and attribution methods, assesses projected and realized outcomes, and translates complex data into clear investment recommendations. This work supports portfolio prioritization, benefits realization, executive reporting, and measurable business impact.

Requirements

Bachelor’s degree in Finance, Economics, Engineering, Analytics, or a related quantitative field
8+ years of experience in financial analysis, management consulting, business value strategy, corporate strategy, or a data-driven advisory function
Experience evaluating the financial and operational value of technology, analytics, automation, or business transformation initiatives
Knowledge of financial modeling, investment analysis, baseline development, and benefits realization practices
Proficiency with analytical and business intelligence tools such as Excel, Power BI, Tableau, SQL, or similar platforms

Nice To Haves

MBA or advanced degree in Finance, Economics, Engineering, Analytics, or Business
Experience in oil and gas, energy, or another asset-intensive industry, with knowledge of operational and capital value drivers
Experience supporting AI, advanced analytics, or digital transformation programs, including measurement and attribution of business value
Familiarity with AI portfolio governance, product lifecycle management, and benefits realization practices

Responsibilities

Develop and maintain the enterprise AI value measurement framework, including valuation methods, baselines, success measures, and reporting standards
Establish business-case and valuation standards and partner with Product Owners and business sponsors to develop, validate, and challenge financial models and value assumptions.
Develop fit-for-purpose valuation approaches including NPV, IRR, scenario analysis, productivity and capacity value, production uplift, capital efficiency, risk avoidance, decision-quality improvements, and other operational measures appropriate to the use case.
Standardize value measurement across operational efficiency, revenue optimization, safety, risk reduction, capital productivity, and workforce effectiveness
Evaluate projected and realized value throughout the AI product lifecycle and recommend whether investments should continue, scale, pivot, or stop based on evidence of business impact.
Define appropriate methods for attributing realized outcomes to AI interventions, including baselines, comparison groups, operational controls, and other analytical approaches needed to distinguish true impact from correlation or external factors.
Partner with the AI Portfolio Lead and business stakeholders to integrate value scoring and economic analysis into prioritization, sequencing, funding, and investment decisions
Develop executive business cases, dashboards, scorecards, and board-level reporting on portfolio performance, business impact, assumptions, attribution, and risks
Translate complex financial and operational data into clear, actionable insights for executive and business stakeholders
Analyze gaps between forecasted and realized value to improve assumptions, measurement practices, attribution methods, and future investment decisions
Influence portfolio and investment decisions through objective, data-driven recommendations and constructive challenge of unsupported value assumptions