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M&A Quant Advisory – Vice President - Investment Banking - New York

Goldman Sachs

New York, NY · $125k–$250k a year · Posted August 19, 2026

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  • Python
  • SQL
  • Machine learning
  • Java
  • M&A

About the job

Corporate title: Vice President.

M&A Quant Advisory – Vice President - Investment Banking

The M&A Quant Advisory team is an integral part of the Goldman Sachs Mergers & Acquisitions (“M&A”) advisory business, responsible for developing quantitative models and technologies to solve complex business problems. As a key pillar of the firm’s M&A business, members of M&A Quant Advisory team use their mathematical and scientific training to advise clients on transactions, identify market opportunities, and help answer complex and data-driven questions. The team has a broad mandate, working closely with our banking teams to pitch and execute mergers and separations across sectors, market caps, and geographies.

Investment Banking Strats are both investment bankers and innovators who create analytics and scalable technology platforms that will shape the future of investment banking and how we connect with clients. Direct participation in client interactions, deal executions, and other core commercial activities allows us to be in the optimal position to develop technical innovations that create economic leverage and differentiate the firm. We ensure maximum technical efficacy by encouraging fluency in the latest quantitative models, data science, data engineering, and software platforms through peer learning, MOOC-like curated learning, and online training resources.

Our team members are quantitative engineers, financial engineers, and data scientists who share a passion for investment banking and the financial markets.

Job Summary & Responsibilities

We are looking for an Vice President to join the Investment Banking M&A Quant Advisory team in New York. This is a banking role which predominantly covers the M&A and industry coverage groups within Investment Banking.

The position involves solving business, data, and technology-related problems across the business, using large and complex financial datasets, and working in tandem with Investment Bankers across different industry and product groups. The role requires a combination of the following competencies: an understanding of the financial markets, M&A, equity and debt products, strong quantitative modelling skills, strong communication skills with non-technical clients and bankers, data and statistical analysis including machine learning, and software engineering.

A successful candidate must act as a local liaison with our global team, and interact with the Classic Banking, Capital Solutions Group, and Global Markets teams. We expect them to be self-led, entrepreneurial, and capable of managing the delivery and adoption of key products.

Responsibilities

Develop and deliver actionable insights and solutions for internal and external clients, including deal performance evaluation, competitive landscape analysis, and execution strategy.

Communicate the team’s analyses and recommendations clearly to Investment Banking clients, tailoring content for non-technical audiences.

Design and implement advanced quantitative and analytical methodologies to identify and prioritize new transaction opportunities.

Build and maintain analytical codebases in Python (and other relevant languages), leveraging machine learning and statistical techniques.

Source, build, and maintain high-quality datasets from multiple vendors by partnering with data providers and designing robust data pipelines, database schemas, and storage/integration solutions; deliver curated datasets aligned to distinct business use cases.

Basic Qualifications

Bachelor’s or advanced degree in a quantitative/ STEM discipline (e.g., Mathematics, Computer Science, Engineering, Statistics etc.)

Strong quantitative / analytic reasoning and problem-solving abilities

Strong technical and computer programming skills in an Object-oriented programming language such as Python or Java

Strong data management skills in data querying languages including SQL, MongoDB, and NoSQL, and extracting large quantities of data from different data sources

Strong oral and written communication skills

Strong interpersonal skills; desire and ability to play on a team

Strong interest in finance, investment banking, and the capital markets

Results-oriented work ethic based upon responsibility, enthusiasm, and pride in work

Preferred Qualifications

5+ years of quantitative modeling and development experience

5+ years of working experience in finance, investment banking and / or capital markets