Data Scientist – Private Equity Value Creation

Wyatt Partners; New York (NY); On-site; USD 120,000 - 150,000; Full time

Job summary

A private equity firm in New York is looking for a Principal Data Scientist to lead data-driven insights across portfolio companies. You'll analyze data to identify opportunities for improvement and grow a small team. Ideal candidates will have 4-6 years of relevant experience, strong skills in Python and R, and a background in consulting or private equity.

Qualifications

• 4–6 years’ experience as a Data Scientist or similar role, ideally in consulting or private equity.
• Proven ability to use data science to solve complex business problems.
• Strong communication and presentation skills to influence stakeholders.

Responsibilities

• Collect, clean, and analyze structured and unstructured datasets.
• Develop and maintain dashboards and KPIs for performance monitoring.
• Collaborate with teams to design data-backed strategies for value creation.

Skills

Data analysis

Data visualization

Machine learning

Statistical analysis

Education

Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field

Master’s degree preferred

Tools

Python

R

SQL

Excel

Power BI

Tableau

Job description

Data Scientist – Private Equity Value Creation

You’d join this firm as Principal Data Scientist in the Private Equity Value Creation team. You will play a pivotal role in driving data-driven insights across portfolio companies. You will be responsible for extracting, analyzing, and interpreting data to identify opportunities for operational improvement, growth, and value creation. This role requires close collaboration with investment professionals, portfolio management teams, and external partners to influence strategic and operational outcomes.

Job progression in this role would see you build out a small team beneath you, which would then allow to shift focus to internal initiatives aimed at advancing the firm’s use of data, AI, and machine learning to improve investment performance and decision-making.

Whilst this firms Portco’s are quite varied by sector, as a general rule they tend to be Business Services companies in the Mid Market.

Key Responsibilities

• Collect, clean, and analyze structured and unstructured datasets from portfolio companies and external sources.
• Develop and maintain dashboards, KPIs, and metrics to monitor operational and financial performance.
• Collaborate with operations and investment teams to identify areas of improvement and design data-backed strategies for value creation.
• Develop forecasting, financial, and operational models to assess scenarios and strategic initiatives.
• Build compelling data visualizations and reports to communicate insights effectively to senior leadership and portfolio management teams.
• Support portfolio companies in building their own data science and analytics capabilities, including mentoring and knowledge sharing.
• Stay updated on emerging trends in data science, machine learning, and AI, applying them to improve value creation initiatives.
• Assist in developing internal tools and systems to optimize private equity investment performance.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field; Master’s degree preferred.
• 4–6 years’ experience as a Data Scientist or similar role, ideally within consulting, private equity, or corporate value creation.
• Proven ability to use data science to solve complex business problems with measurable outcomes.
• Strong proficiency in Python, R, SQL, and Excel; experience with data visualization tools such as Power BI or Tableau.
• Hands-on experience with cloud-based data platforms (e.g., Databricks, Microsoft Synapse, AWS, or Azure).
• Knowledge of machine learning techniques and their practical business applications.
• Excellent quantitative and qualitative analytical skills with strong attention to detail.
• Strong communication and presentation skills with the ability to influence senior stakeholders.
• Ability to work independently while contributing effectively to cross-functional teams.
• Familiarity with financial modeling and valuation techniques is a plus.