VP, M&A Quant Advisory — Data-Driven Deals Leader

Goldman Sachs; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

A global investment bank is seeking a Vice President for the M&A Quant Advisory team in New York. This role involves tackling data and technology-related challenges while leveraging quantitative models to drive business insights. Applicants should possess strong analytical, communication, and programming skills, with a background in finance and investment banking. Responsibilities include delivering client solutions, maintaining analytical frameworks, and designing methodologies for transaction analysis, all while collaborating with various teams within the organization.

Qualifications

• Strong quantitative/analytic reasoning and problem-solving abilities.
• Ability to manage and analyze large datasets.
• Proven experience communicating complex analyses to diverse audiences.

Responsibilities

• Develop actionable insights for clients including deal performance.
• Communicate analyses clearly to investment banking clients.
• Design advanced quantitative methodologies for new transaction opportunities.
• Maintain analytical codebases leveraging machine learning and statistical techniques.
• Build high-quality datasets from various vendors and design robust data pipelines.

Skills

Quantitative modeling skills

Communication skills with non-technical clients

Data analysis

Machine learning

Software engineering

Education

Bachelor’s or advanced degree in a quantitative/STEM discipline

Tools

Python

SQL

MongoDB

NoSQL

Java

Job description

A global investment bank is seeking a Vice President for the M&A Quant Advisory team in New York. This role involves tackling data and technology-related challenges while leveraging quantitative models to drive business insights. Applicants should possess strong analytical, communication, and programming skills, with a background in finance and investment banking. Responsibilities include delivering client solutions, maintaining analytical frameworks, and designing methodologies for transaction analysis, all while collaborating with various teams within the organization.