AlpInvest Embedded Data Scientist

Position Summary

Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly with investment professionals across Primaries, Secondaries, and Co-Investments. This role sits at the intersection of investing, data science, artificial intelligence, and product development. The successful candidate will work alongside deal teams to develop analytical frameworks, generate proprietary investment insights, and build scalable products that enhance investment decision‑making.

Unlike traditional data science roles, this position requires the ability to operate as both a technical expert and a strategic thought partner. The ideal candidate can move seamlessly between developing machine learning models and engaging with investment professionals on questions related to manager selection, fund evaluation, portfolio construction, investment pricing, and market intelligence. This individual will help advance several strategic initiatives, including GP Scoring, One Day Pricing, AI‑powered diligence workflows, portfolio intelligence, and market signal generation.

• Partner directly with investment professionals across Primaries, Secondaries, and Co‑Investments to support live investment opportunities.
• Translate investment questions into analytical frameworks, models, and actionable insights.
• Conduct quantitative analyses to evaluate fund managers, investment strategies, portfolio performance, and market opportunities.
• Present findings and recommendations to investment teams and senior leadership.

• Develop and enhance proprietary GP Scoring methodologies used to evaluate private equity managers.
• Build scalable analytical products that integrate into Alp Invest's investment workflows.
• Design and deploy machine learning, statistical, and AI‑driven solutions to improve investment decision‑making.
• Contribute to the development of One‑Day Pricing capabilities for LP interest transactions.
• Support creation of market intelligence, portfolio monitoring, and company intelligence products.

• Develop and improve predictive models leveraging structured and unstructured investment datasets.
• Apply modern AI techniques, including LLMs, agent‑based workflows, and retrieval systems, to investment research and diligence processes.
• Collaborate with engineering and product teams to product ionize analytical capabilities.
• Identify opportunities to automate workflows and improve scalability across investment processes.

• Build strong relationships with investment professionals and become a trusted advisor across business lines.
• Gather requirements, prioritize opportunities, and translate business needs into technical solutions.
• Communicate complex analytical concepts to both technical and non‑technical audiences.
• Help drive adoption of data science products and insights throughout the organization.

• 8+ years of overall relevant technical experience.
• Experience in Data Science, Machine Learning, Quantitative Analytics, Applied AI, or related fields, with a proven track record of success.
• Experience building and deploying production‑grade analytical products and models.
• Demonstrated ability to work directly with senior business stakeholders and solve complex business problems.
• Experience operating in highly ambiguous environments and managing multiple priorities simultaneously.
• Strong programming skills in Python and experience with modern data science libraries and frameworks.
• Deep understanding of statistical modeling, machine learning, experimentation, and predictive analytics.
• Experience working with structured and unstructured datasets at scale.
• Familiarity with cloud‑based analytics environments and modern data platforms.
• Experience applying generative AI, LLMs, or agent‑based systems is strongly preferred.
• Experience with in private equity, asset management, investment management, alternative investments, financial services, or investment technology.
• Familiarity with investment performance metrics, portfolio analytics, fund structures, or manager evaluation frameworks.
• Experience developing products that combine quantitative analysis with business decision‑making.

The compensation range for this role in New York is $180,000 to $200,000 base salary. In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.