• Ensure operational efficiency and excellence by leading and/or assisting in the creation and documentation of new or revised department procedures. • Recommend appropriate departmental objectives that support the company strategy and objectives and create solutions to address business and operational challenges. • Lead working groups and/or committees to set goals and execute on implementation to address process or procedural gaps. • Partner with internal and external stakeholders to optimize Data Management technology, processes, and standards. • Participate in project and department budget development and responsible for effective management of budgets for assigned projects and staff. • Participate in the evaluation and selection of data system vendors to enhance Data Management processes, e.g. EDC, IRT, ePRO, eConsent. • Contribute to the financial success of the department and company by effectively managing financial aspects of assigned programs, including but not limited to Work Orders, Change Orders, study forecasting and budgeting. • Identify and quantify resource requirements for ongoing and future projects; Interview, hire, onboard and train new staff as appropriate. • Supervise, mentor, provide leadership and maintain positive team morale; facilitates conflict resolution. • Oversee development of direct reports by setting and tracking individual objectives and key results to support department and company strategies and objectives. • Evaluate training needs and conduct performance reviews for assigned staff. • Set priorities and oversee activities for assigned staff. • Ensure Data Management deliverables for projects assigned meet/exceed project/study team expectations regarding quality, time, and cost. • Serve as the subject matter expert on data collection strategy and handling of study data for assigned programs and effectively liaise with programming to ensure clinical databases are designed in a standard, accurate, complete, and consistent format to produce datasets that are conducive to analysis and a possible regulatory submission. • Proactively identify data management project issues, manage risks, and alert Senior Department Management with a view to remedial action. • Interact/liaise with other departments to ensure a high level of client satisfaction through successful issue resolution and execution of projects. • May work with other departments and analysts on special projects to ensure company end to end processes and technologies are efficient and effective, work seamlessly together and deliver improved customer value. • May represent Data Management at business development, sponsor, or other professional meetings. • Assist the business development team with RFIs, RFPs and project pricing.

• Design and implement measurement and evaluation frameworks to understand the impact of Trust defense, and uncover opportunities for improvement • Collaborating closely with cross-functional partners, lead the design and analysis of experiments and quasi-experiments in environments where standard A/B testing is challenging. • Build and iterate on statistical and Bayesian models that quantify risk, estimate treatment effects, and surface measurement gaps; provide causal interpretation of signals surfaced by ML systems • Generate deep insights on the effectiveness of Trust defenses and translate them into clear strategic recommendations for product roadmap and policy decisions • Deliver robust, leadership-ready research with rigorous analysis, compelling data visualizations, and clear narratives; effectively communicate complex methodological tradeoffs to both technical and non-technical audiences across product, engineering, policy and operations • Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes

• Build and deploy production AI/ML systems for trust integrity, including feature engineering, model development and evaluation, thresholding, error analysis and end-to-end model lifecycle management. This includes working with NLP and LLM-based models in real production settings. • Partner with inference data scientists to conduct rigorous quantitative analyses, applying working knowledge of causal inference to interpret results, assess impact, and identify gaps and opportunities to improve content quality and trust outcomes. • Deliver clear, well-structured research findings with compelling data visualizations and rigorous analysis to drive alignment and action with cross-functional partners in product, engineering and operations • Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes

Role Description As a Data Scientist working on Causal Inference in Community Support (CS), you will have the opportunity to collaborate with a strong team of engineers, product managers, designers, and operation agents to enable personalized, fair, and exceptional experiences for guests and hosts using advanced causal inference analysis. You'll work on high-impact projects like: - Designing rigorous experiments and quasi-experiments to measure the causal impact of CS product launches and drive data-informed launch decisions. - Building causal ML models to optimize Make Goods budget allocation and maximize business impact. - Conducting causal inference analyses to quantify the long-term effects of product changes and uncover heterogeneous treatment effects. - Delivering strategic insights on quality-cost tradeoffs, empowering leadership to deliver the best possible support experience to our community. Qualifications - 2+ years of industry experience in a quantitative analysis role with a Master's degree in a quantitative field (statistics, economics, computer science, etc.), or PhD in relevant fields. - Strong knowledge of causal inference and experimental design. - Strong knowledge of Bayesian modeling and statistical inference. - Hands-on experience building and deploying statistical or ML models in production environments. - Skilled in statistical programming (Python/R) and database usage (SQL). - Proven ability to communicate clearly and effectively to audiences of varying technical levels. - Ability to translate complex findings into compelling narratives that drive impact. - Excellent project management, communication, and collaboration skills. Requirements - Design and implement causal inference frameworks and statistical models to measure the impact of interventions, evaluate system performance, and uncover opportunities for improvement. - Build, evaluate, and iterate on causal ML models that power high-stakes decisions, applying best practices across the full model lifecycle from feature engineering to production deployment. - Develop frameworks to analyze tradeoffs between competing objectives (accuracy, coverage, user experience, and operational cost), and propose strategies to improve overall effectiveness. - Build strong relationships with cross-functional partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation. - Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed, data-driven decision-making. - Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes. Benefits - Base pay range: $151,000 — $175,000 USD. - This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Company Description Airbnb is a mission-driven company dedicated to creating a world where anyone can belong anywhere. Our Community Support (CS) team is at the heart of that mission—delivering seamless, 10-star customer service experiences complemented by world-class, personalized human support that empowers hosts and guests at every step of their journey.