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

Goldman Sachs • New York, NY

3d

About The Position

Goldman Sachs’ Strats business unit is a world leader in developing quantitative
models and technologies to solve complex business problems. Working within the
firm’s trading, sales, banking, and asset management divisions, strats use their
mathematical and scientific training to create financial products, advise
clients on transactions, measure risk, and identify market
opportunities. Investment Banking Strats are involved in marketing, structuring,
pricing, and executing transactions for large corporations and institutions in
the capital markets and M&A. We develop state-of-the-art quantitative and
analytical methods for advising clients, and we build financing and
risk-management solutions across products and industries.

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.

Requirements

• 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

Nice To Haves

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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level