Data Science Consultant

Job Title: Data Science Consultant

Location: New York, NY (Hybrid)

Compensation: $200,000 - $300,000 total compensation

Role: Data Science Consultant

A leading global investment firm is hiring a Senior Data Scientist to support investment diligence and portfolio value creation initiatives across a diverse international portfolio. The team operates at the intersection of private equity, analytics, and applied AI, partnering directly with investment professionals and portfolio company leadership teams on high-impact commercial and operational challenges.

This role combines fast-paced investment diligence work with hands-on value creation initiatives across multiple industries and business models. The environment is highly collaborative, execution-oriented, and designed for individuals who enjoy solving ambiguous business problems with data-driven thinking.

Why This Role Matters

Data science is deeply embedded in the investment and operational decision-making process across the firm.

This role will directly influence how investment teams:

• Evaluate live acquisition opportunities
• Identify operational inefficiencies and growth levers
• Drive AI and analytics adoption across portfolio companies
• Improve commercial performance and customer retention
• Translate data into an actionable business strategy

You’ll work directly with deal teams, operating executives, and senior leadership in a high-visibility environment where analytical insights can materially shape investment decisions and portfolio outcomes.

What You’ll Do

• Support live investment diligence processes by conducting rapid, decision-grade analyses across commercial, operational, and market datasets
• Partner directly with investment teams to identify growth opportunities, operational risks, and commercial insights that influence investment decisions
• Build pragmatic analytics and AI solutions for portfolio companies, focusing on measurable operational and commercial impact
• Develop proofs-of-concept and applied data science initiatives tied to areas such as churn prediction, revenue optimization, customer retention, pricing strategy, and demand forecasting
• Work closely with portfolio company leadership teams to ensure analytical solutions are successfully adopted into existing business processes and workflows
• Evaluate build-versus-buy opportunities and help determine when third-party AI or SaaS solutions are more commercially effective than internal development
• Leverage a wide variety of structured and unstructured datasets, including financial market intelligence, consumer behavior, web traffic, operational, labor market, and sentiment data sources

Ideal Candidate

• Has strong hands-on data science experience within consulting, private equity, analytics, or commercially-oriented environments
• Demonstrates the ability to independently frame ambiguous business problems rather than simply execute predefined technical tasks
• Brings strong Python-based analytical and modeling capabilities with experience implementing production-quality analyses and prototypes
• Understands how to identify areas of business value creation through data, including revenue optimization, operational efficiency, customer retention, or commercial performance improvement
• Has experience working with modern cloud data platforms such as Databricks or Snowflake
• Is comfortable building dashboards and communicating insights using tools such as Tableau or Power BI
• Can clearly communicate business impact and analytical recommendations to both technical and non-technical stakeholders
• Thrives in fast-paced, high-accountability environments with multiple concurrent priorities and executive visibility

About Us

People In AI partners with high-growth AI and machine learning companies to help build exceptional technical teams. We work closely with investment firms, startups, and scaling organizations, building meaningful AI and analytics capabilities, and helping candidates connect with high-impact opportunities through a transparent and streamlined process.