Data Scientist 2

JLL•San Francisco, CA

3d•Onsite

About The Position

JLL empowers you to shape a brighter way. Our people at JLL and JLL Technologies are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Data Scientist - JLL Falcon AI Platform About the job JLL (NYSE: JLL) is a leading professional services and investment management firm specializing in real estate. We are a Fortune 500 company with operations in over 80 countries, a workforce of nearly 100,000 individuals around the world, and annual revenue of almost $20B. Within JLL, we are part of JLL Technologies, a strategic business group whose mission is to leverage technology to increase the value and liquidity of the world's buildings. We established a centralized AI Platform team to democratize AI capabilities enterprise-wide while maintaining security, compliance, and quality standards. Our mission is to empower JLL's 100,000+ employees to innovate and drive productivity through AI—embedded directly into their daily workflows. JLL Falcon is our enterprise AI platform that makes AI capabilities simple, reliable, and accessible across every commercial real estate workflow. We deliver conversational AI (JLL GPT), intelligent assistants (Outlook Assistant), and developer-specific tools. Our vision is to enable AI agents that can complete tasks autonomously—shifting from assistive AI to agentic AI that reduces manual work and accelerates decision-making. As a Data Scientist on the JLL Falcon team, you'll be working on critical platform capabilities that enable AI agents, evaluation frameworks, and cutting-edge AI technologies at enterprise scale. This role is based in San Francisco, where you'll work closely with your data science and product partners to drive the platform's AI capabilities forward. Highlights: Cutting-edge AI work: Build and enable platform capabilities for AI agents, working with modern technologies including RAG, LangChain, LangGraph, advanced evaluation frameworks, and more. Enterprise impact: Your work will directly impact how 100,000+ employees interact with AI across JLL's global operations. Small team, big resources: Work in a focused, collaborative team with the resources and support of a Fortune 500 company. Critical role: This position is essential to the team's roadmap and represents a unique opportunity to shape the future of AI at JLL.

Requirements

Master's degree (PhD preferred) in data science, computer science, mathematics, AI, machine learning, or related STEM fields
2+ years of industry experience in a data science, researcher, or machine learning role
Experience working on data science projects end-to-end including planning, data exploration, data processing, model development, evaluation, model deployment to production, and project presentation to stakeholders
Hands-on experience with frameworks like LangChain, LangGraph, or similar tools for building and orchestrating LLM-powered applications
Experience with rigorous evaluation and assessment of AI models and systems
Experience working on data science projects end-to-end including planning, data exploration, data processing, model development, evaluation, model deployment to production, and project presentation to stakeholders

Nice To Haves

Experience with multi-agent systems and agent communication protocols - Advantage
Knowledgeable in commercial real estate sector - Advantage
Eagerness to contribute to the broader scientific community via teaching, open source contributions, blogging, publishing, organizing events, etc. - Advantage

Responsibilities

Develop, evaluate, and continuously improve genAI using engineering and advanced data science approaches
Design and develop intelligent agent architectures using frameworks like LangChain and LangGraph for autonomous decision-making and task execution
Build comprehensive evaluation frameworks for models, assistants, and agents, including stable evaluation datasets and core metrics
Implement advanced Retrieval-Augmented Generation (RAG) techniques to enhance agent knowledge and capabilities
Partner with multi-functional peers from engineering, product, and business to deliver AI solutions
Communicate results orally and in writing to facilitate collaboration and team growth.