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Remote Private Equity Data Science Jobs (NOW HIRING)

Weekday AI

Private Equity Associate

$100 - $200/hr

This role offers a unique opportunity to combine traditional private equity and investment banking skill sets with innovative AI technologies in a collaborative, fully remote environment.

HedgeServ

Private Equity Supervisor

New York, NY · On-site +1

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... HedgeServ supports employees through a variety of offerings, including remote and hybrid working ...

HedgeServ

Private Equity Supervisor

Dallas, TX · On-site +1

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... HedgeServ supports employees through a variety of offerings, including remote and hybrid working ...

HedgeServ

Private Equity Supervisor

Raleigh, NC · On-site +1

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... HedgeServ supports employees through a variety of offerings, including remote and hybrid working ...

Mercor

Private Equity Analyst

San Francisco, CA · Remote

$130/hr

Private Equity Expert Type: Contract Compensation: $130/hour Location ... Remote Duration: Minimum four weeks Commitment: 10+ hours/week Role Responsibilities * Evaluate ...

Jobgether

You will work in a fast-paced, data-driven environment where technology and analytical expertise ... Flexible remote working arrangements with consideration for academic commitments and exam schedules.

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All JobsRemote Private Equity Data Science Jobs

Remote Private Equity Data Science information

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$37.5K

$122.7K

$196.5K

How much do remote private equity data science jobs pay per year?

As of Jun 30, 2026, the average yearly pay for remote private equity data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are some of the unique challenges faced by data scientists working remotely in private equity, and how can they be addressed?

Remote data scientists in private equity often encounter challenges such as accessing sensitive financial data securely, collaborating across time zones, and communicating complex analyses to investment teams. To address these, firms typically implement robust cybersecurity protocols, schedule regular virtual meetings to maintain alignment, and use collaborative tools like shared dashboards or project management platforms. Proactively setting clear expectations and maintaining open lines of communication with both technical and non-technical team members are key to success in this fast-paced, data-driven environment.

What is the difference between Remote Private Equity Data Science vs Remote Investment Analyst?

AspectRemote Private Equity Data ScienceRemote Investment Analyst
Required CredentialsDegree in Data Science, Finance, or related fields; proficiency in data analysis toolsDegree in Finance, Economics, or related fields; strong analytical skills
Work EnvironmentCollaborates with data teams, often in tech or finance firms, using data analysis and modelingResearches market trends, evaluates investments, and prepares reports, often in finance firms
Employer & Industry UsagePrivate equity firms, investment funds, consulting firmsAsset management firms, investment banks, hedge funds

Remote Private Equity Data Science focuses on analyzing large datasets to inform investment decisions using advanced analytics, while Remote Investment Analysts evaluate market data and financial reports to recommend investments. Both roles require strong analytical skills but differ in technical focus and daily tasks.

What is Remote Private Equity Data Science?

Remote Private Equity Data Science involves applying data analysis, machine learning, and statistical techniques to support private equity firms in investment decision-making, portfolio management, and risk assessment—all while working remotely. Professionals in this field analyze large datasets, build predictive models, and generate insights to help firms identify valuable investment opportunities and improve operational efficiency. Working remotely allows data scientists to collaborate with global teams and access diverse data sources using cloud-based tools. This role typically requires strong quantitative skills, knowledge of finance, and experience with programming languages such as Python or R.

What are the key skills and qualifications needed to thrive as a Remote Private Equity Data Scientist, and why are they important?

To thrive as a Remote Private Equity Data Scientist, you need strong quantitative analysis skills, proficiency in statistics, and experience with financial modeling, typically supported by a degree in data science, finance, or a related field. Expertise in programming languages like Python or R, familiarity with machine learning libraries, and experience with data visualization tools and databases are commonly required, as are certifications in data science or finance. Exceptional problem-solving abilities, communication skills, and the capacity to work independently and collaboratively in remote settings set top professionals apart. These skills ensure accurate analysis of investment opportunities, clear insights for decision-makers, and effective teamwork across distributed environments.
More about Remote Private Equity Data Science jobs
What cities are hiring for Remote Private Equity Data Science jobs? Cities with the most Remote Private Equity Data Science job openings:
What are the most commonly searched types of Private Equity Data Science jobs? The most popular types of Private Equity Data Science jobs are:
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What job categories do people searching Remote Private Equity Data Science jobs look for? The top searched job categories for Remote Private Equity Data Science jobs are:
Remote Private Equity Data Science jobs near you
Infographic showing various Remote Private Equity Data Science job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, 9% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Private Equity Associate

Weekday AI

Remote

$100 - $200/hr

Part-time

Posted 5 days ago

Key responsibilities

  • Develop, review, and refine financial models to support AI training programs, ensuring technical accuracy and alignment with industry standards.

  • Translate market research, investment memos, and due diligence findings into structured AI training datasets and learning modules.

  • Evaluate and improve AI-generated financial analyses, identifying gaps in reasoning, modeling assumptions, or valuation methodologies.

Job description

This role is for one of our clients
Compensation: $100 - $200/hour-pay
Join a forward-thinking team at the intersection of private equity and artificial intelligence. As a Private Equity Associate supporting AI training initiatives, you will apply your investment and financial modeling expertise to help shape next-generation AI-driven solutions for financial analysis, due diligence, and portfolio management.
This role offers a unique opportunity to combine traditional private equity and investment banking skill sets with innovative AI technologies in a collaborative, fully remote environment.
Requirements
Key Responsibilities
  • Develop, review, and refine financial models to support AI training programs, ensuring technical accuracy and alignment with industry standards.
  • Translate market research, investment memos, and due diligence findings into structured AI training datasets and learning modules.
  • Partner with cross-functional stakeholders to convert complex financial concepts into clear, actionable AI training inputs.
  • Evaluate and improve AI-generated financial analyses, identifying gaps in reasoning, modeling assumptions, or valuation methodologies.
  • Contribute strategic insights to enhance the performance and effectiveness of AI-powered private equity and investment tools.

Required Qualifications
  • Minimum 2 years of experience in private equity and/or investment banking with a strong background in financial modeling.
  • Demonstrated expertise in market research, due diligence, valuation, and investment analysis.
  • Strong analytical capabilities with meticulous attention to detail.
  • Exceptional written and verbal communication skills, with the ability to clearly explain complex financial concepts.
  • Proven ability to manage stakeholders and collaborate across teams.
  • Strong problem-solving skills and the ability to work independently in a structured, deadline-driven environment.

Preferred Qualifications
  • Experience working with or training AI/ML systems in a financial context.
  • Advanced proficiency in Excel and financial modeling best practices.
  • Exposure to AI initiatives within private equity or investment banking environments.

Apply