Asset & Wealth Management - Private Equity Data Science - Associate - London

The role:

Join our Private Equity Data Science team and contribute to DSML and AI initiatives across the full lifecycle of the investment process. The Data Scientist will be responsible for the design, development, and implementation of quantitative and data-driven models to drive innovation and productivity for origination, due diligence, and investment performance. The data science team sits alongside the Goldman Sachs Private Equity Deal Teams and works closely with the Goldman Sachs Value Accelerator and portfolio company management teams.

Key Responsibilities:

• Leverage sophisticated statistical, mathematical, and programming skills to analyse complex datasets, support the investment processes, and drive quantifiable commercial value.
• Partner with Deal Teams to define and deliver data-driven origination initiatives
• Deliver quantitative analyses through investment due diligence; translating complex data into comprehensive analyses assessing potential risk and opportunities in tight timelines
• Partner strategically with portfolio company management teams to drive data and AI initiatives for value creation
• Partner with GS Engineering to lead development and implementation of data-centric tools, enhancing our investment processes and supporting our deal and fundraising teams
• Stay up-to-date with the latest developments in AI, ML, and related fields to continuously improve the division's AI capabilities

Qualifications, experience, and attributes:

• PhD or equivalent in a quantitative field such as Mathematics, Computer Science, Physics or in a related field
• 2+ years of relevant experience applying quantitative methods to commercial problems
• Strong programming skills (Python, SQL) and experience using the basic data science libraries (e.g. pandas, scikit-learn)
• High-level of proficiency in mathematics, statistics, and data science theory
• Proven experience implementing sophisticated data science techniques, handling large datasets, translating data into actionable business insights
• Commercial experience with a strong track record of quantitative problem solving and realised commercial impact
• Excellent written and verbal communication and collaboration skills with a strong growth mindset

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