Responsibilities:

• Develop comprehensive real estate strategy documents that synthesize market analysis, financial modeling, and location recommendations for CFO and executive leadership review
• Lead strategic portfolio planning including scenario modeling for growth, market entry/exit decisions, and long-term footprint optimization
• Create executive-level presentations and decision memos that translate complex real estate data into clear strategic recommendations
• Conduct in-depth market analyses including competitive positioning, labor market dynamics, talent availability, and cost-of-occupancy comparisons across target markets
• Build and maintain sophisticated financial models for real estate decisions including NPV analysis, lease vs. buy scenarios, and total cost of occupancy projections
• Partner with Finance on capital planning, real estate budgeting, and investment justification for major portfolio decisions

Portfolio & Program Oversight:

• Develop location strategy frameworks that align real estate decisions with business unit requirements, talent strategy, and corporate objectives
• Oversee occupancy planning and demand forecasting efforts, translating headcount projections into actionable space requirements and timing recommendations
• Direct lease administration strategy including portfolio risk assessment, lease restructuring opportunities, and critical obligation management
• Establish portfolio performance metrics and reporting frameworks that provide executive visibility into real estate investments and outcomes
• Partner with external advisors (brokers, consultants, legal) to execute strategic initiatives and negotiate favorable terms
• Identify portfolio optimization opportunities including consolidation, expansion, or repositioning strategies that enhance operational efficiency and reduce costs

Team Leadership:

• Manage and develop a team of two direct reports: a Real Estate Program Manager and an Occupancy Planning/Lease Administration specialist
• Set clear goals and priorities for the team, ensuring alignment with broader real estate and company objectives
• Provide coaching, mentorship, and professional development opportunities to build team capabilities
• Foster a collaborative, high-performance culture that emphasizes quality, accountability, and continuous improvement
• Allocate resources effectively across strategic initiatives and operational demands

You may be a good fit if you:

• Have 10+ years of progressive experience in corporate real estate strategy, portfolio management, or real estate finance, with at least 3-5 years in a people management role
• Have a proven track record of developing and presenting real estate strategies to executives
• Possess sophisticated financial modeling skills including NPV, IRR, scenario analysis, and total cost of occupancy methodologies
• Have deep expertise in market analysis including labor economics, competitive positioning, and location strategy development
• Are an exceptional writer who can synthesize complex analyses into compelling strategic narratives and executive-ready documents
• Have demonstrated success building and leading high-performing teams
• Have experience managing portfolios of significant scale and complexity across multiple geographies
• Can operate with autonomy and drive strategic initiatives with minimal direction
• Have strong executive presence and can confidently present recommendations to senior leadership
• Thrive in fast-paced, high-growth environments where you can build processes and frameworks from the ground up

Strong candidates may also:

• Have experience in high-growth technology companies navigating rapid scaling challenges
• Hold an MBA or advanced degree in real estate, finance, or related field
• Have relevant certifications such as CoreNet MCR or CCIM
• Bring consulting experience from firms specializing in corporate real estate strategy
• Have experience with international market entry and global portfolio optimization
• Have led major strategic initiatives such as headquarters relocations, portfolio consolidations, or market expansions

Annual compensation range for this role is $275,000-$275,000 USD.

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The Economic Research team at Anthropic studies the economic implications of AI on individual, firm, and economy-wide outcomes. We build scalable systems to monitor AI usage patterns and directly measure the impact of AI adoption on real-world outcomes. We publish research and data that is clear-eyed about the economic effects of AI to help policymakers, businesses, and the public understand and navigate the transition to powerful AI.

In this role, you will work closely with teams across Anthropic,including Data Science and Analytics, Data Infrastructure, Societal Impacts, and Public Policy,to build scalable and robust data systems that support high-leverage, high-impact research. Strong candidates will have a track record building data processing pipelines, architecting & implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating ambiguity, and demonstrating an eagerness to develop their own research & technical skills.

Responsibilities:

• Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.
• Expand privacy-preserving tools to enable new analytic functionality to support research needs.
• Design and implement novel data systems leveraging language models (e.g., CLIO) where traditional software engineering patterns don't yet exist.
• Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.
• Contribute to the strategic development of the economic research data foundations roadmap
• Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure
• Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions
• Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.
• Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission

You might be a good fit if you have:

• Experience working with Research Scientists and Economists on ambiguous AI and economic projects
• Experience with building and maintaining data infrastructure, large datasets, and internal tools in production environments.
• Experience with cloud infrastructure platforms such as AWS or GCP.
• Take pride in writing clean, well-documented code in Python that others can build upon
• Are comfortable making technical decisions with incomplete information while maintaining high engineering standards
• Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization
• Have a track record of using technical infrastructure to interface effectively with machine learning models
• Have experience deriving insights from imperfect data streams
• Have experience building systems and products on top of LLMs
• Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders
• A passion for Anthropic's mission of building helpful, honest, and harmless AI and understanding its economic implications.
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
• Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.

Strong candidates may have:

• Background in econometrics, statistics, or quantitative social science research
• Experience building data infrastructure and data foundations for research
• Familiarity with large language models, AI systems, or ML research workflows
• Prior work on projects related to labor economics, technology adoption, or economic measurement

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