Capital allocation AI Expert

Weekday AI

4h•$100 - $120•Remote

About The Position

This role is for one of our clients. We are seeking a Capital Allocation AI Expert to drive data-informed investment decisions across the organization. This role sits at the intersection of finance, strategy, and advanced analytics, focusing on optimizing how capital is deployed to maximize long-term value. You will evaluate investment opportunities, guide build vs. buy decisions, and prioritize initiatives under resource constraints using AI-driven insights and rigorous financial frameworks.

Requirements

Bachelor’s or Master’s degree in Finance, Economics, Engineering, Data Science, or a related field.
2–8 years of experience in capital allocation, investment analysis, strategy consulting, or a similar role.
Strong financial modeling skills with a deep understanding of ROI metrics (NPV, IRR, etc.).
Experience applying AI/ML techniques to business decision-making or forecasting.
Proven ability to structure and solve complex problems under uncertainty.
Familiarity with build vs. buy evaluation frameworks and strategic trade-off analysis.
Strong analytical tools proficiency (e.g., Python, SQL, Excel, or similar).
Excellent communication and stakeholder management skills.

Nice To Haves

Experience in high-growth or technology-driven environments.
Exposure to optimization algorithms or resource allocation models.
Background in corporate strategy, venture investing, or product prioritization.

Responsibilities

Analyze a wide range of investment opportunities, including product development, technology adoption, acquisitions, and operational improvements.
Build and maintain financial models to assess ROI, IRR, NPV, and payback periods.
Leverage AI and predictive analytics to enhance forecasting accuracy and scenario planning.
Translate complex analyses into clear, actionable recommendations for stakeholders.
Develop structured frameworks to assess whether capabilities should be built internally or acquired externally.
Incorporate cost, time-to-market, scalability, strategic control, and risk factors into decision-making models.
Use data-driven insights to quantify trade-offs and support leadership in making informed choices aligned with long-term business goals.
Design prioritization models that balance strategic impact, financial return, and resource availability.
Apply optimization techniques and AI tools to rank initiatives across competing demands.
Work closely with cross-functional teams to ensure alignment between strategic priorities and execution capacity.
Implement and utilize machine learning models and decision-support systems to enhance capital allocation processes.
Continuously improve data pipelines, model accuracy, and reporting capabilities.
Identify opportunities to automate repetitive analysis and improve decision speed without compromising quality.
Partner with finance, product, engineering, and leadership teams to gather inputs, validate assumptions, and align on priorities.
Communicate insights effectively to both technical and non-technical audiences, ensuring transparency in decision-making.
Track the performance of funded initiatives against projected outcomes.
Conduct post-investment reviews to refine models and improve future allocation decisions.
Establish feedback loops to ensure continuous improvement.