Robinhood
finance
DataScientist,ML(Agentic,CX)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist, ML (Agentic, CX) at Robinhood. Skills: machine learning development, multi-agent orchestration, evaluation pipelines, personalization systems, agent architectures. lead machine learning development across the customer experience stack. models and prompts that power multi-agent orchestration”
Industry & Context.
Sharp problem-solvers; working through ambiguous problems
What They're Looking For.
Must Have
Python skills, SQL skills, experience building and evaluating machine learning systems end to end, experience with agent-based AI systems, including reasoning loops, tool use, memory, retrieval-augmented generation, and orchestration, experience designing experiments and applying causal inference methods, including A testing and measurement design
Nice to Have
Experience building and evaluating agent-based systems for production use, Experience developing recommendation, ranking, or personalization systems at scale, Experience working on AI products in regulated industries such as financial services
What You'll Do.
lead machine learning development across the customer experience stack
models and prompts that power multi-agent orchestration
evaluation pipelines that measure model quality at scale
personalization systems that determine when and how to engage customers
strengthen feedback loops between live systems and offline evaluation
apply advanced AI techniques in a regulated environment
Build and deploy machine learning models for customer support systems
including intent classification
and multi-agent orchestration
Design evaluation frameworks using LLM-based review methods
and automated quality metrics to identify regressions before customer impact
and personalization models that support proactive outreach and tailored AI experiences
Translate advances in agent architectures into production systems
partnering with engineering on prompt design
Develop systems that maintain response quality and reliability at scale while working with product
and compliance partners
How You'll Work.
Team & Collaboration
partner closely with product and engineering; partnering with engineering on prompt design, retrieval systems, tool use, memory, and orchestration; working with product, engineering, legal, and compliance partners
Full Job Description
Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Platforms Data Science team sits at the intersection of customer experience and trust, building the intelligence that powers how Robinhood supports its customers. The team develops systems that safeguards customers and the platform while making every interaction smarter: from the in-app AI assistant that helps customers research, trade, and manage their portfolios, to the AI-powered support chatbot that resolves issues autonomously, to the machine learning systems that detect and prevent fraud and abuse in real time. These systems rely on evaluation frameworks and guardrails that maintain reliability and safety across the platform. You will work with product engineering, product management, and ML infrastructure teams to deliver production-ready AI systems at scale. Join a team where your work directly shapes how customers interact with Robinhood! As a Data Scientist, Agentic (CX), you will lead machine learning development across the customer experience stack. This includes models and prompts that power multi-agent orchestration, evaluation pipelines that measure model quality at scale, and personalization systems that determine when and how to engage customers. You wil
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