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Private Equity Machine Learning Jobs (NOW HIRING)

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... Our proprietary platform, enhanced by machine learning and robotic process automation, gives ...

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... Our proprietary platform, enhanced by machine learning and robotic process automation, gives ...

... private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech ... Our proprietary platform, enhanced by machine learning and robotic process automation, gives ...

Private Equity Analyst

Boston, MA · On-site

$80K - $120K/yr

A commitment to learning and professional growth is essential, as the firm promotes from within and fosters a collaborative environment. Salary Range: $80,000 - $120,000 / Year DOE Private Equity ...

As a Private Equity Associate supporting AI training initiatives, you will apply your investment ... learning modules. * Partner with cross-functional stakeholders to convert complex financial ...

Machine Learning Engineer (Austin, TX) Striveworks is a leader in Machine Learning Operations for ... Equity - Owners have a history of another startup that turned to IPO in 5 years. The company offers ...

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Competitive salary, cash bonus, equity structure, and 401k with employer contributions * Excellent ...

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Private Equity Machine Learning information

See salary details

$47K

$100.2K

$143K

How much do private equity machine learning jobs pay per year?

As of Jun 8, 2026, the average yearly pay for private equity machine learning in the United States is $100,180.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Private Equity Machine Learning professional, and why are they important?

To thrive as a Private Equity Machine Learning professional, you need a strong background in finance, quantitative analysis, and machine learning, typically supported by degrees in finance, computer science, or related fields. Proficiency in programming languages such as Python or R, experience with machine learning libraries (e.g., TensorFlow, scikit-learn), and familiarity with financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help bridge technical insights with investment strategies. These capabilities are crucial for identifying data-driven investment opportunities, optimizing portfolio performance, and supporting rigorous, evidence-based decision-making.

What is Private Equity Machine Learning?

Private Equity Machine Learning refers to the application of machine learning algorithms and data analytics in the private equity industry. Professionals in this field use advanced data science techniques to analyze large datasets, identify investment opportunities, optimize portfolio management, and improve due diligence processes. By leveraging machine learning, private equity firms can gain deeper insights into market trends, predict company performance, and make more informed investment decisions. This approach helps firms stay competitive in a data-driven financial landscape.

How does a Private Equity Machine Learning professional typically collaborate with investment teams during deal sourcing and due diligence?

In a Private Equity Machine Learning role, you’ll work closely with investment teams by developing and deploying data-driven models to identify attractive investment opportunities and assess potential risks. You may help automate the screening of large datasets to uncover patterns, forecast performance, or flag anomalies that inform deal sourcing. During due diligence, your analyses support valuation, growth projections, and operational insights, often requiring clear communication of technical findings to non-technical colleagues. This collaborative environment allows you to directly influence investment decisions while gaining exposure to both analytical and business aspects of private equity.

Which 3 jobs will survive AI?

Private Equity professionals, especially those involved in deal sourcing, due diligence, and portfolio management, are likely to continue thriving as AI tools assist but do not replace strategic decision-making. Data scientists and machine learning engineers will remain essential for developing and maintaining AI models used in investment analysis. Additionally, compliance officers and legal experts will continue to be vital for navigating regulatory requirements in the evolving financial landscape.

What is the difference between Private Equity Machine Learning vs Data Scientist in Private Equity?

AspectPrivate Equity Machine LearningData Scientist in Private Equity
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with machine learning frameworksDegree in Statistics, Data Science, or related fields; strong programming skills
Work EnvironmentFocus on developing ML models for investment analysis, often in finance-focused teamsAnalyze data, build models, and generate insights for investment decisions within private equity firms
Employer & Industry UsagePrivate equity firms, hedge funds, financial institutionsPrivate equity firms, investment banks, financial consultancies

While both roles involve data analysis and programming, Private Equity Machine Learning specialists focus on developing advanced algorithms to predict investment outcomes, whereas Data Scientists in Private Equity analyze data to support investment decisions. The roles often overlap but differ in technical focus and application within the private equity industry.

Private Equity Manager

Private Equity Manager

HedgeServ

Dallas, TX • On-site

Full-time

Posted 28 days ago


Job description

At HedgeServ, we're redefining what's possible in fund administration. With more than $700 billion in assets under administration, we partner with the world's most forward-thinking investment managers - across private equity, private credit, endowments, hedge funds and more - to deliver seamless, tech-enabled solutions that drive performance.
Our proprietary platform, enhanced by machine learning and robotic process automation, gives clients real-time insights and unmatched control over their operations. Alongside our technology, we offer award-winning service through our team-based approach -- led by a deeply experienced team of industry experts. Our solutions span the full investment lifecycle, including fund accounting, middle office, risk, compliance, tax, and investor services.
We're a future-focused company, empowering our people through a robust career development framework, clear career trajectories with structured learning paths, training, and progression plans. We invest in leadership development and in our collaborative culture, creating space for talent to grow. Our corporate values - Relationships, Support, Innovation, and Expertise - create a sense of shared purpose and belonging, and we recognize our employees sit at the core of our success. We continue to innovate and evolve through our employees, working together to achieve our shared vision and mission.
HedgeServ supports employees through a variety of offerings, including remote and hybrid working arrangements, and fully paid comprehensive health and well-being benefits. We've been recognized as an employer of choice, earning a top 100 workplaces designation.
Founded in 2008, HedgeServ has grown into a global organization with over 2,000 experts across the globe, with offices in the United States, Grand Cayman, Ireland, Poland, Bulgaria, Luxembourg, the Philippines, and Australia. We've earned numerous accolades, including Top Overall Administrator, along with #1 rankings for providing alternative asset services in Accounting, Technology, Client Service, Investor Services, Alternative Fund Expertise, Reporting, and Regulatory Expertise.
This role will be hybrid in either our Dallas, TX or Raleigh, NC office. Visa sponsorship will not be offered at this time.
Job Description
A Private Equity Manager will be required to manage the closed end fund accounting process within the guidelines and procedures provided by HedgeServ and under the supervision and guidance of a Private Equity Director and Managing Director. They will manage the timely and accurate delivery of NAV calculations. They will assist in the development of client relationships and will require a detailed understanding of the service requirements for closed end fund administration.
Responsibilities
The below list is not finite and may be added to. The combination of tasks required to be executed will vary depending on both client structure, client requirements and business needs.
Responsible for the day-to-day management of the Private Equity team including:
  • Capital Call and Distribution Processing
  • Preparation of net asset value calculations and financial statements
  • Fee calculations and profit and loss allocations
  • Waterfall creation and maintenance
  • Performance reporting including IRRs
  • Ad hoc client and investor reporting
  • Managing client relationships involving interaction with both the client and the relevant Private Equity Director to ensure consistency of service
  • Ensure the assigned accounting team operates within the clearly defined and documented control environment
  • Manage and develop client teams of up to 10 employees
  • Resolve fund accounting enquiries escalated by Supervisor or Administrator
  • Develop and improve workflows and procedures
  • Manage the audit process ensuring timely and successful completion of fund audits
  • Manage and complete client onboarding and transitions
  • Manage fund accounting recruitment, training and performance evaluations
  • Establish and maintain effective working relationships with other stakeholder groups

HedgeServ operates a client focused structure which provides a wide range of experience to all levels of employees. As such a Private Equity Fund Accounting Manager should be flexible and willing to adapt.
Pre-requisite Knowledge, Skills and Experience
  • Minimum of 5 years' experience working in a Hedge Fund Administration firm with at least 3 of those at Supervisor level is desired. Alternative Hedge Fund or Private Equity Fund experience will be considered
  • Accounting, Economics, Finance, Mathematics or Business Degree
  • Intention to actively pursue a professional accounting qualification (ACCA, CIMA, CPA, ACA), if not already started, part qualified or qualified, would be an advantage but is not required
  • Strong verbal and written communication skills
  • Good people manager with the ability to coach and develop a team
  • Strong analytical and problem-solving skills
  • Ability to be flexible and work effectively both within a team structure or independently
  • Strong inter-personal skills with the ability to influence at all levels of the organization
  • Strong systems, product and process knowledge - Investran experience ideal