Modelling Data Scientist, Vice President - AI Labs

BlackRock•San Francisco, NY

22h•$167,500 - $225,000•Hybrid

About The Position

AI Labs Overview For more than three decades, BlackRock has combined world-class talent and technology to redefine what's possible in asset management. Today, AI is reshaping every aspect of our industry, from investments and client experiences to operations, risk management, and product innovation. BlackRock AI Labs sits at the center of that transformation. AI Labs is BlackRock's advanced AI science and engineering organization. We partner with teams across the firm to solve some of the most complex and consequential challenges in financial services, applying generative AI, machine learning, optimization, and statistics to deliver measurable business impact. Our mission is simple but ambitious: combine human and machine intelligence to revolutionize asset management. What sets AI Labs apart is our ability to move from idea to impact. We are not a research lab detached from the business, nor are we a traditional software engineering organization. We are a hybrid team of scientists and engineers who build solutions that run at scale in production environments and create capacity for our business partners. From AI-powered investment insights and risk management solutions to next-generation agentic workflows and enterprise AI platforms, our work is helping to shape the future of BlackRock. Our teams work on some of the firm's highest priority strategic initiatives, including large-scale generative AI systems, intelligent agents, predictive analytics, optimization engines, operational risk solutions, and AI platforms that accelerate innovation across BlackRock. We help define best practices, establish technical standards, and enable teams throughout the organization to adopt AI safely, effectively, and at scale. AI Labs has offices in New York, Edinburgh, Atlanta, San Francisco and Seattle. We are looking for candidates with unique backgrounds and diverse skill sets with fresh perspectives to accelerate and amplify our efforts to make an impact at BlackRock. Description As a data scientist, you will collaborate with a distributed team of outstanding scientists, engineers, and investment professionals to develop methodologies to solve a corporate-wide set of client, investor, and operational problems. Solutions developed often use multiple subject areas, including Generative AI, machine learning, and optimization, and combine original methods with pioneering solutions available in industry and academia. You will be responsible for the entire solution lifecycle, from initial scoping, research and prototyping, scaled implementation, productionalization in collaboration with engineering, and clearing internal review processes.

Requirements

PhD in a quantitative field (machine learning, artificial intelligence, mathematics, statistics, economics, computer science, physics, engineering, or related field) with 4+ years of professional experience OR MS degree in a quantitative field plus 7+ years of professional experience in machine learning, artificial intelligence, or other aspects of the AI / data science and agent development process.
Strong familiarity with Python programming.
Strong theoretical background in and practical experience using AI, machine learning, optimization, or statistical techniques.
Experience assessing performance of machine learning methods and agentic systems: benchmark construction, metric design, and statistically sound measurement of quality, safety, and reliability.
Ability to work within a team environment, and to collaborate and communicate across cross-functional groups.

Nice To Haves

Depth in one or more research areas relevant to our work, e.g. LLM reasoning, reinforcement learning, machine learning, statistical modeling, or quantitative optimization.
Academic publications, preprints, or open-source contributions.
Experience building and deploying AI agents and agentic workflows using open-source frameworks (e.g. LangGraph, Pydantic AI, OpenAI Agents SDK), agent platforms (e.g. Amazon Bedrock, Microsoft Agent Framework, Claude Agent SDK), or comparable tools, including standards such as Model Context Protocol (MCP) for connecting agents to tools and data.
Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory.
Experience with machine learning libraries (e.g. PyTorch), cloud platforms (AWS, Azure, GCP), and the analysis of financial or economic data.
Experience building production-grade solutions, and leading technical projects or managing

Responsibilities

Be accountable for the delivery of major projects and key initiatives for AI Labs.
Work with stakeholders to translate business needs into well-scoped AI/ML solutions.
Design, build, and evaluate AI agents and agentic workflows - including tool use, memory, and multi-step reasoning - on top of large, complex datasets.
Rapidly prototype agentic solutions using cutting-edge AI/ML tools, agent frameworks, orchestration platforms, and foundation model APIs.
Work with engineers and stakeholders to build production-grade solutions that are reliable, scalable, and operate in compliance with firm-wide processes, including agent observability, guardrails, and evaluation pipelines.
Define and maintain evaluation frameworks (evals) to measure agent quality, safety, and reliability in production.
Present technical work clearly to senior leaders and general audiences, and promote thought leadership through white papers, publications, and presentations.