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Blackstone

Global alternative asset manager and investor

Data Science Engineering - Vice President

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeNew York, NY, USA$175k - $200k /yrIn-person

About the Job

Requirements

  • An undergraduate degree in a technical discipline, such as computer science, data science, applied mathematics, operations research, or engineering, is required.
  • At least 6 years of relevant experience in a data-driven setting as a machine learning engineer, data scientist, software engineer, or data engineer is required.
  • Expert proficiency in Python and SQL is required; experience with 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, is required.
  • Experience with statistical and machine learning modeling, such as regression, forecasting, and classification, and taking such models to production is required.
  • A track record of owning model deployment into user-facing products such as web applications, APIs or MCP servers, automated reporting, and Excel-based tools is required.
  • A strong foundation in statistics and mathematics is required.
  • Experience creating financial analytical models and working with financial data is required.
  • Strong communication and project management skills as a technical lead on projects are required.
  • Ability to communicate technical concepts effectively to non-technical audiences, both orally and in writing, is required.
  • Ability to work independently and meet deadlines with minimal oversight is required.
  • Ability to work independently and lead and coordinate a team on larger projects is required.

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 across Real Estate and Private Equity to translate underwriting, diligence, asset management, and portfolio monitoring questions into models and products, and incorporate their feedback to improve model quality.
  • Build and own 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.
  • 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, thoughtful code reviews, and constructive feedback.
  • Work across BXDS and the Blackstone Technology Innovations group to build core infrastructure that allows the team to scale.

Desired Qualifications

  • 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.
  • Experience with strongly typed and/or functional programming languages.

About the Company

Blackstone

Global alternative asset manager and investor

Blackstone is a global manager of alternative assets, pooling capital from institutions and individuals to invest in private markets across private equity, real estate, and credit. It uses funds and strategies, including BREIT and BCRED, to deploy capital into real estate, loans, and private securities, generating income and growth for investors. The firm differentiates itself by its scale, global reach, and broad product lineup that provides access to private markets through financial professionals. Its goal is to build and manage industry-leading businesses and assets to deliver durable, long-term returns for investors.

Company size
5,001-10,000
Company stage
IPO
Headquarters
New York City, New York
Founded
1985

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