Contract Investment Banker Generative AI - Finance - Kensho

Kensho is S&P Global’s hub for AI innovation and transformation. With expertise in machine learning, natural language processing, and data discovery, we develop and deploy novel solutions to innovate and drive progress at S&P Global and its customers worldwide. Kensho 's solutions and research focus on business and financial generative AI applications, agents, data retrieval APIs, data extraction, and much more.

At Kensho , we hire talented people and give them the autonomy and support needed to build amazing technology and products. We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one another is open, honest, and efficient. We dedicate time and resources to explore new ideas, but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful.

Role Overview

We are seeking experienced Investment Banking professionals to serve as domain experts on a contract basis, contributing to the development of generative AI tools for financial modeling and transaction analysis.

In this role, you will leverage your real-world investment banking experience to help AI systems learn how to perform core banking tasks at a professional standard. You will create, evaluate, and refine transaction-oriented analyses that reflect how bankers actually think about valuation, deal structure, and execution. This is not a live deal or client-facing role; rather, you will help define and encode best-in-class banking workflows for AI systems.

Key Responsibilities

Produce high-quality investment banking deliverables used to train and evaluate AI systems, including:

Valuation analyses (DCF, trading comps, precedent transactions)

M&A and capital markets financial models

Accretion/dilution and pro forma analyses

Transaction scenarios and sensitivity analyses

Build financial models that adhere to industry-standard conventions, structure, and presentation

Decompose complex transaction logic into clear, step-by-step reasoning that can be learned by AI systems

Review and assess AI-generated banking outputs for:

Financial accuracy and internal consistency

Soundness of assumptions

Professional formatting and analytical rigor

Provide detailed feedback to improve model reliability, realism, and edge-case handling

Collaborate asynchronously with product, research, and engineering teams to refine task definitions and evaluation criteria

Ideal Candidate Profile

3-7 years of experience in investment banking, corporate finance, or transaction-focused advisory roles

Strong technical foundation in:

Financial modeling and valuation

M&A and capital markets transactions

Accounting and finan