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NEXTMOVEFDE careers · United States
The Carlyle Group

AlpInvest Embedded Data Scientist

AI summary of the role

Embedded data scientist role within Carlyle's AlpInvest investment platform, partnering directly with deal teams across primaries, secondaries, and co-investments.

What you’ll do

  • Partner with investment professionals to translate investment questions into analytical frameworks and actionable insights.
  • Develop and enhance proprietary GP Scoring methodologies and contribute to One-Day Pricing capabilities.
  • Design and deploy machine learning, statistical, and AI-driven solutions to improve investment decision-making.
  • Apply modern AI techniques including LLMs, agent-based workflows, and retrieval systems to investment research.

What you’ll bring

  • 8+ years of overall relevant technical experience.
  • Bachelor's degree or higher in a quantitative discipline (MS/PhD/MBA preferred).
  • Strong programming skills in Python and experience with modern data science libraries.
  • Deep understanding of statistical modeling, machine learning, and predictive analytics.

Technologies

Python · Machine Learning · LLMs · Agent-based workflows · Retrieval systems · Generative AI · Cloud analytics · Statistical modeling · Predictive analytics

Source and classification

Internal deployment & tooling · Evidence for this classification:

Position Summary: Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly with investment professionals across Primaries, Secondaries, and CoInvestments. 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
More from the job description

Position Summary: Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly with investment professionals across Primaries, Secondaries, and CoInvestments. 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, OneDay Pricing, AI-powered diligence workflows, portfolio intelligence, and market signal generation. Primary Responsibilities Investment Analytics & Decision Support 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. [... source excerpt omitted ...] ern AI techniques, including LLMs, agent-based workflows, and retrieval systems, to investment research and diligence processes. Collaborate with engineering and product teams to productionize analytical capabilities. Identify opportunities to automate workflows and improve scalability across investment processes. Stakeholder Engagement 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 a [... source excerpt omitted ...] red Experience in Data Science, Machine Learning, Quantitative Analytics, Applied AI, or related fields, with a proved 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 an

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