Blackstone Data Science Product Engineering, Vice President

Blackstone • New York, NY

6d • $175,000 - $200,000

About The Position

Blackstone is hiring a data science engineering vice president for Blackstone Data Science (BXDS), focused on creating and deploying agentic AI and machine learning models that support investment decision-making across Real Estate and Private Equity. Working with BXDS data scientists and investors, the role builds and improves agentic and statistical models and owns their delivery to investors through web applications, MCP servers, automated reports, and Excel tools. The role also designs and implements the cloud architecture, data engineering infrastructure, and data science tooling behind these products. Applications span underwriting, deal screening and diligence, asset- and portfolio-company-level forecasting, portfolio monitoring, and reasoning over unstructured investment materials.

The position works across Real Estate and Private Equity investment teams, BXDS data scientists, and Blackstone Technology Innovations to build infrastructure that enables BXDS to scale. The ideal candidate is a hands-on technical leader at the intersection of agentic AI, machine learning, and software engineering, with a track record of building robust production systems, strong analytical and financial modeling skills, and the ability to mentor junior team members.

Requirements

• Undergraduate degree in a technical discipline, such as computer science, data science, applied math, operations research, or engineering.
• At least 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 Python and SQL.
• 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, such as regression, forecasting, or classification, and taking models to production.
• Track record of owning 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.
• Ability to communicate technical concepts effectively to non-technical audiences, both orally and in writing.
• Self-starter able to work independently and meet deadlines with minimal oversight.
• Ability to work independently and lead and coordinate a team on larger projects.

Nice To Haves

• Proficiency in strongly typed and/or functional programming languages.
• 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 a desire to solve novel technical challenges.
• Ability to balance multiple projects and efficiently meet goals in a dynamic environment.

Responsibilities

• Own 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 to translate underwriting, diligence, asset management, and portfolio monitoring questions into models and products, and incorporate feedback to improve model quality.
• Build and own channels through which models reach users, including web applications, MCP servers, 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 outputs are accurate, traceable, and interpretable by investment professionals.
• Mentor junior team members through high-quality code implementation, code reviews, and constructive feedback.
• Work across BXDS and Blackstone Technology Innovations to build core infrastructure that allows the team to scale.

Benefits

• Comprehensive health benefits, including medical, dental, vision, and FSA benefits.
• Paid time off.
• Life insurance.
• 401(k) plan.
• Discretionary bonuses.
• Certain employees may be eligible for equity and other incentive compensation at Blackstone’s sole discretion.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior