Job Description

About this role

We are looking for a Senior Data Scientist (6+ years of experience)to join our data science team working on advanced AI-driven solutions This is primarily an individual contributor role, with responsibility for owningend-to-end ownership of complex modeling / AI problem areasand technical ownership of AI capabilities critical to the product

The role focuses on the research, prototyping, evaluation, and improvement of AI solutions, with hands-on work across LLM-based systems, including agent-style workflows and retrieval-augmented generation (RAG)whereappropriate You will work end-to-end: collaborating with stakeholders and product managers to define problems,buildingandvalidatingprototypes, presenting findings to diverse audiences, and supporting engineering teams during implementation and production rollout.

Key Responsibilities

End-to-end AI solution ownership

• Own AI projects or functional modules from problem definition through prototype validation and production support

• Partner with product managers and business stakeholdersto translate real-world problems into clearly scoped data science and AI initiatives.

• Independently plan and execute research, experimentation, and iteration cycles in ambiguous problem spaces.

• Design AI solutions with a system‑level perspective, ensuring scalability, maintainability, and long‑term sustainability.

Applied AI, LLMs, and agentic systems

• Design and prototype LLM-powered solutions, including RAG-based systemsand agent-like workflows (e.g.tool use, orchestration, multi-step reasoning).

• Contribute to defining system behavior, scope, and constraints, with attention to quality, robustness, and operational considerations.

• Stay current with emerging AI techniques and apply them pragmatically to solve business problems.

Evaluation, validation, and performance improvement

• Build andmaintainevaluation frameworksto assess AI system performance (accuracy, reliability, relevance, robustness, safety).

• Develop quantitative and qualitative metrics, benchmarks, and testing approaches tovalidateprototypes and track improvements.

• Analyze existing solutions toidentifygaps and drive continuous, data-driven performance enhancements.

Collaboration and communication

• Work closely with data scientists, engineers, and product teamsto ensure smooth transition from prototype to production.

• Clearly communicate methods, assumptions, results, and limitations to technical and non-technical audiences

• Support engineering teams during implementation by clarifying evaluation criteria, edge cases, and expected system behavior.

• Serve as a technical authority and actively mentor junior data scientists, shaping best practices in experimentation, evaluation, and AI system design.

Ways of working

• Contribute actively within an Agile / SCRUMdevelopment environment.

• Apply good engineering hygiene in research and prototype code to enable reproducibility and collaboration.

Required Qualifications

• 6+ yearsof experience in data science, applied machine learning, or a closely related role.

• Strong mathematical, statistical, and machine learning foundations, including probability, statistics, optimization, and model evaluation.

• Proven ability to select, apply, and critically evaluate ML models and algorithms for real-world problems.

• Strong Pythonskills for analysis, modeling, experimentation, and prototyping.

• Strong SQLskills for data exploration, transformation, and analytical workflows.

• Excellent analytical thinking and problem-structuring abilities; comfortoperatingindependently with loosely defined goals.

• Experience using Gitfor version control and collaborative development.

• Strong English communication skills, both written and verbal.

Preferred Qualifications (Strong Plus)

• Hands-on experience with LLMs, including prompt/system design and building real-world applications.

• Experience with RAG systems, including retrieval strategies, chunking, evaluation, and performance tuning.

• Experience designing or contributing to agent-style AI systemsand familiarity with concepts such as agent evaluation, guardrails, and reliability testing.

• ML modeling experience (e.g.supervised learning, ranking, classification) beyond exploratory analysis.

• Understanding ofsoftware engineering best practices, including testing strategies and CI/CD concepts.

• Experience working in Azureor similar cloud environments.

• Familiarity with Snowflake(and optionally Snowflake AI) as part of a modern data stack.

• Experience collaborating closely with domain experts; financial domain exposure is a plus but notrequiredfor strong technical candidates.

What Success Looks Like in This Role

• You independently deliver high-quality AI prototypesand evaluation frameworks for a defined subdomain or application module.

• You proactively define scope, success metrics, and experimentation plans, helping shape architecture and design decisions.

• Your evaluation approaches enable reliable comparison, regression prevention, and continuous improvement of AI solutions.

• Engineering teams can confidentlyproductionizeyour work thanks to clear designs, metrics, and collaboration.

• Over time, you raise the technical maturity of AI development and evaluation practices within the team.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’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.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.