About this roleDescriptionAs 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.
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.
Required experience- 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.
Additional experience we value: you don't need all of these. We're looking for depth in some areas and the range to grow into the rest.
- 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
For New York, NY and SF4-San Francisco - 400 Howard Street Only the salary range for this position is USD$167,500.00 - USD$225,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
Our benefitsTo help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work modelBlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person - aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
Guidance on AI use for candidatesAt BlackRock, AI has long been part of how we work - enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we've provided
guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
