Blackstone Data Science Product Engineering, Vice President

Blackstone is the world’s largest alternative asset manager. Blackstone seeks to deliver compelling returns for institutional and individual investors by strengthening the companies in which the firm invests. Blackstone’s over $1.3 trillion in assets under management include global investment strategies focused on real estate, private equity, credit, infrastructure, life sciences, growth equity, secondaries and hedge funds. Further information is available at www.blackstone.com . Follow @blackstone on LinkedIn , X (Twitter) , and Instagram .

BXDS Product Engineering, Vice President

Agentic AI and ML Deployment | Real Estate and Private Equity

Blackstone is the world's largest private capital fund. Their $1.2T in assets under management includes investment vehicles focused on private equity, real estate, public debt and equity, infrastructure, life sciences, growth equity, opportunistic, non-investment grade credit, real assets and secondary funds.

Blackstone's Operating Team is a team of dedicated executives and advisors with decades of combined operational experience and expertise. They form a world-class operating platform that partners with Blackstone's investment and portfolio company management teams to advise and support across a wide range of operational initiatives, corporate functions, and business subject areas. The group aims to leverage Blackstone's scale and expertise to support management in driving transformational growth and value-creation for all stakeholders across the investment lifecycle.

Blackstone Data Science (BXDS) is the firm-wide team that uses advanced analytics and statistical methods to make the group better investors and business operators. It consists of data scientists, engineers, and strategists who collaborate closely with investment teams to analyze complex datasets, develop predictive and analytical models, build production-quality data flows, and advise on smarter data utilization. BXDS is part of the firm's Operating Team. They work hand-in-hand with management teams to build more valuable businesses and accelerate growth.

Position Summary

Blackstone is looking to hire a data science engineering vice president to be an integral member of BXDS, focused on the creation and deployment of the agentic and machine learning models that support better investment decision-making across the firm's Real Estate and Private Equity businesses. Working side by side with BXDS data scientists and investors, the role builds and continuously improves agentic and statistical models, and owns how those models are delivered into investors' hands through web applications, MCP servers, automated reports, and Excel tools. It also involves designing and implementing the cloud architecture, data engineering infrastructure, and data science tooling behind these products, applied to a variety of investment challenges, from underwriting, deal screening, and diligence to asset- and portfolio-company-level forecasting, portfolio monitoring, and reasoning over unstructured deal materials, leases, board materials, and market research.

The selected candidate will work across Real Estate and Private Equity investment teams, BXDS data scientists, and the Blackstone Technology Innovations group, building the core infrastructure that powers the Blackstone Data Science team to scale. The ideal candidate is a versatile technical leader who excels at the intersection of agentic AI, machine learning, and software engineering, and who takes ownership of their work. This role demands a hands-on, detail-oriented professional with a proven track record of building robust, production-grade systems, backed by strong analytical thinking and financial modeling expertise. The role requires mentoring junior team members, providing thoughtful code reviews, and constructive feedback to drive the group's development and success.

Key Responsibilities

Own the end-to-end delivery of agentic and machine learning models across Real Estate and Private Equity, from prototype through production, user adoption, and ongoing support

Partner with BXDS data scientists to productionize, scale, and continuously improve agentic and statistical models, including feature pipelines, model serving, retraining, and versioning

Work with investment professionals across Real Estate and Private Equity to translate underwriting, diligence, asset management, and portfolio monitoring questions into models and products, incorporating their feedback to improve model quality

Build and own the channels through which models reach users: web applications, MCP servers that expose models, data, and tools to AI assistants and agents, automated reports, and Excel-based tools

Design and build agentic workflows and retrieval and reasoning systems over unstructured investment content, including offering memoranda, leases, CIMs, board materials, and market research

Implement data engineering best practices, and ML and LLMOps tooling on AWS, applying modern CI/CD practices.

Establish evaluation, monitoring, and guardrails for agentic and statistical models so that outputs are accurate, traceable, and interpretable by investment professionals

Mentor junior team members through high-quality code implementation, thoughtful code reviews, and constructive feedback

Work across BXDS and the Blackstone Technology Innovations group to build the core infrastructure that allows the team to scale

Qualifications

Required

Undergraduate degree in a technical discipline (e.g. computer science, data science, applied math, operations research, or engineering) required

6+ years of relevant experience in a data driven setting as a machine learning engineer, data scientist, software engineer, or data engineer

Expert proficiency in programming and querying languages including Python and SQL, strongly typed and/or functional languages is a plus

Hands-on experience building and deploying agentic AI and machine learning applications, including agentic workflows, retrieval-augmented generation, model orchestration, MLOps, and evaluation frameworks

Experience with statistical and machine learning modeling (e.g., regression, forecasting, classification) and taking such models to production

Track record of owning the deployment of models into user-facing products such as web applications, APIs/MCP servers, automated reporting, and Excel-based tools

Strong foundation in statistics and mathematics

Experience creating financial analytical models and working with financial data

Strong communication and project management skills as a technical lead on projects

Effectively communicate technical concepts to non-technical audiences effectively both orally and in writing

Self-starter who can work independently and meet deadlines with minimal oversight

Capable of working independently as well as leading and coordinating a team on larger projects

Preferred

Experience in private equity, real estate, or another investment domain, with familiarity with deal, portfolio-company, property, lease, or market data

Experience building or integrating MCP servers, LLM tool-calling, or agent frameworks

Experience with analytical methodologies and desire to solve novel technical challenges

Excellence in balancing multiple projects and efficiently meeting goals in a dynamic environment

The duties and responsibilities described here are not exhaustive and additional assignments, duties, or responsibilities may be required of this position. Assignments, duties, and responsibilities may be changed at any time, with or without notice, by Blackstone in its sole discretion.

Expected annual base salary range:

$175,000 - $200,000

Actual base salary within that range will be determined by several components including but not limited to the individual's experience, skills, qualifications and job location. For roles located outside of the US, please disregard the posted salar