Data Science Consultant / Senior Data Science Consultant
(Applied AI, Data Science & Private Equity)
$300,000 - $350,000 Cash Compensation
Location: New York – minimum 3 days per week in office, with 4 days preferred
The Company
A major global private equity investor is expanding its Data Science capability in New York. The team operates across the investment lifecycle, combining high-stakes due diligence with hands-on AI and analytics work inside portfolio companies.
Data Science is closely connected to investment and value-creation teams, giving the function direct exposure to commercially important decisions.
The Opportunity
This role sits at the intersection of Data Science, AI, investing, and business strategy. You will influence live investment decisions before deals close and then help portfolio companies identify and validate high-value AI and analytics opportunities.
The focus is on proving business value quickly rather than building large-scale production infrastructure.
The Role
You will split your time roughly evenly between pre-deal diligence and post-deal value creation. That means moving from investment questions and commercial hypotheses into hands-on modeling, MVP development, and executive-level recommendations.
You will work directly with investment professionals and portfolio company stakeholders across a constantly changing set of industries and problems.
What You’ll Do
Build analytical and machine learning models that support live investment diligence and commercial decision-making.
Investigate businesses to assess growth opportunities, risks, customer behavior, and potential applications of AI.
Help shape AI roadmaps and prioritize use cases based on expected value and feasibility.
Develop MVPs and proofs of concept that demonstrate whether Data Science or AI can materially improve business outcomes.
Apply predictive and prescriptive modeling, agentic AI, optimization, simulation, and broader analytics to commercial problems.
Partner with portfolio company stakeholders to move priority use cases from strategy into practical experimentation.
Present technical findings as clear, commercially focused recommendations to senior stakeholders.
What You’ll Bring
Strong hands-on Data Science experience with genuine depth in modeling and applied machine learning.
Strong Python skills and comfort working with modern analytical and data platforms.
The ability to connect technical work to measurable commercial outcomes rather than focusing primarily on engineering complexity.
Experience structuring ambiguous business problems and identifying the right analytical approach.
Clear, concise communication skills and confidence working with senior commercial stakeholders.
Consulting, private equity, strategy, or another high-performance commercial environment is strongly relevant, although technically strong candidates from technology backgrounds can also fit.
For senior candidates, experience managing multiple workstreams and mentoring or leading junior team members.
What This Role Requires
Genuine hands-on modeling and Data Science experience.
Strong understanding of machine learning and applied analytics.
Ability to explain technical work clearly in terms of business value and decision-making.
Comfort operating directly with senior stakeholders in a high-paced environment.
Ability to understand and defend your own technical work, including where AI-assisted development tools are used.
Why Join
Work across both investment diligence and post-investment value creation, giving you unusually broad commercial exposure for a Data Scientist.
Build AI and analytical solutions where the objective is measurable business impact rather than technical complexity for its own sake.
Gain exposure across industries, businesses, datasets, and AI use cases while working directly with investment teams and senior executives.
About People in AI
People in AI is a specialist recruitment partner connecting exceptional AI, machine learning, data, and engineering talent with some of the most ambitious technology companies in the world. We work closely with founders, technical leaders, and hiring teams to represent opportunities accurately and help candidates assess genuine fit.
