AVP/VP, Investment Research, Private Equity, Technology Investment Group

About the role

You will be part of a team that is one of the largest, and most established private equity investors in the world today. You will lead the team's research efforts using advanced analytics, statistical methods, and AI/LLMs to drive investment decisions and ensure we maintain a differentiated view in the market. Moving beyond traditional analysis, you will function as a core partner on investment decisions, collaborating directly with the deal teams to stress-test investment theses and address key investment concerns. This includes direct engagement with prospective technology companies, using data and AI to answer key investment questions, and ultimately driving investment decisions alongside the deal team. Our lean team provides the opportunity for team members to assume significant responsibility at the center of the investment lifecycle.

Responsibilities

• Partner with deal teams to deliver differentiated investment insights, validate core underwriting assumptions and drive investment decisions through a rigorous, quantitative approach
• Take ownership of developing innovative solutions that leverage data/AI to generate differentiated signals that can directly influence investment decisions
• Engage directly with prospective technology companies alongside the deal team to 'supercharge' our investment diligence process. This includes identifying novel methods to evaluate a company's products and fundamental growth drivers, expanding and enhancing the datasets that we have access to, and performing deep-dive technical analysis
• Leverage AI/LLMs to increase the speed and depth of our investment diligence process
• Support the monitoring of our investment portfolio using a rigorous, data-driven approach
• Build strong relationships within the technology and AI community

Requirements

• 4+ years of technical experience (e.g., as a data scientist, data engineer, or in a technical research role); prior experience in a similar role at a venture or growth fund is highly preferred
• Degree(s) in computer science, mathematics, machine learning, engineering, or related quantitative discipline
• Expertise in data science, including experience with the modern data stack (e.g. Snowflake, Databricks, dbt, Tableau, etc.) and the ability to extract, clean, and analyze complicated datasets from diverse sources and formats
• Exceptional command of programming languages such as Python
• Excellent communication skills, with the ability to explain technical results to non-technical stakeholders
• Solid business understanding and judgement
• Attention to detail
• Team player and enjoys working in a collaborative environment
• Highly motivated self-starter and able to work independently
• Interest in investing and venture/growth equity markets

Qualifications or Skills

• 4+ years of technical experience (e.g., as a data scientist, data engineer, or in a technical research role); prior experience in a similar role at a venture or growth fund is highly preferred
• Degree(s) in computer science, mathematics, machine learning, engineering, or related quantitative discipline
• Expertise in data science, including experience with the modern data stack (e.g. Snowflake, Databricks, dbt, Tableau, etc.) and the ability to extract, clean, and analyze complicated datasets from diverse sources and formats
• Exceptional command of programming languages such as Python
• Excellent communication skills, with the ability to explain technical results to non-technical stakeholders
• Solid business understanding and judgement
• Attention to detail
• Team player and enjoys working in a collaborative environment
• Highly motivated self-starter and able to work independently
• Interest in investing and venture/growth equity markets

Benefits

• Flexible work schedule
• Equal opportunity employer

Pay

The anticipated base salary range for this role is between $180,000 and $315,000. Bonuses, which may form a meaningful proportion of the total pay package, are determined based on company and individual performance.

Schedule

Four days per week in the office, with flexibility to choose which days to work from home.