M&A Quant Advisory – Vice President - Investment Banking (Quantitative Engineering)

Location: New York, NY, United States

Salary: USD 125,000–250,000 per year

Company

hirify.global is an investment banking and global financial markets firm.

What you will do

• Develop actionable insights and solutions for internal and external clients, including deal performance evaluations, competitive landscape analyses, and execution strategies.
• Communicate analyses and recommendations clearly to investment banking clients and non-technical stakeholders.
• Design and implement quantitative and analytical methodologies to identify and prioritize transaction opportunities.
• Build and maintain analytical codebases in Python and other relevant programming languages using machine learning and statistical techniques.
• Source and maintain datasets from multiple vendors, designing data pipelines, database schemas, and storage and integration solutions for distinct business use cases.
• Act as a local liaison with global teams and collaborate with Classic Banking, Capital Solutions Group, and Global Markets.

Requirements

• Bachelor’s or advanced degree in mathematics, computer science, engineering, statistics, or another quantitative STEM discipline.
• Strong quantitative reasoning, analytical problem-solving, programming, and data management skills.
• Experience with an object-oriented language such as Python or Java.
• Experience querying and extracting large datasets using SQL, MongoDB, and NoSQL technologies.
• Strong written, oral, and interpersonal communication skills, with the ability to work effectively in teams and communicate with non-technical clients.
• Strong interest in finance, investment banking, and capital markets; 5+ years of quantitative modeling, development, finance, investment banking, or capital markets experience preferred.

Culture & Benefits

• Work across M&A, industry coverage, product, and global banking teams.
• Access peer learning, curated online learning, and training resources covering quantitative models, data science, data engineering, and software platforms.
• Combine client interaction, deal execution, quantitative analysis, and technology innovation.