Role Description More in Common is looking to hire up to two Research Fellows experienced in quantitative and mixed-method full-scope research. Research Fellows will support More in Common’s work across a range of projects related to democracy, public policy, political primaries, polarization, topical political events, social connection, and social cohesion in the U.S. context. This is a 6-month contract role. Ideally, these Research Fellows will be able to work 25-40 hours per week beginning in June/July 2026. This is a US-based role, and the Research Fellow must be authorized to work in the United States. Despite its limited term, this is a fully embedded role working across multiple project teams, with meaningful involvement in research design, analysis, interpretation, and communication. The exact mix of responsibilities for the role will vary depending on the Research Fellow’s background, strengths, and project assignments. The role typically involves: - Designing and programming quantitative and qualitative surveys, including survey experiments - Conducting mixed-method analyses of survey and qualitative data (e.g., from focus groups), including longitudinal and cross-sectional analyses - Segmentation analyses of survey data (e.g., hierarchical cluster analysis, latent class analysis, k-means) - Social media and social listening analysis - Visualizing data (e.g., in R, PowerPoint, Flourish, Canva, etc.) - Synthesizing and communicating findings through memos, reports, presentations, and partner-facing discussions - Developing focus group and interview protocols; leading focus groups and interviews - Communicating findings effectively to nonacademic audiences through presentations and written communications - Meeting with project partners to ascertain needs, incorporate feedback, and deliver results This role reports to one of our Senior Research Managers. The Research Fellows will work closely with other research and communications team members on our U.S. team. Project areas these research fellows will work on include a combination of the following: - Understanding who is connecting across differences through volunteerism/service in their communities, and why - A segmentation of Americans’ policy attitudes - A segmentation of election primary voters - Topical political polling - Other potential projects should funding arrive, including on Americans’ attitudes toward universal national service and political accountability, a political attitudes segmentation of American youth, democratic resilience This opportunity is flexible in terms of location, and remote work will be considered. This role may include occasional U.S. travel. Qualifications - Ph.D. in a related field or equivalent research experience - Deep curiosity about how other people think - Strong sense of respect for differing views - Ability and desire to work across the ideological spectrum - Keen interest in politics and public issues - Strong conviction in making a difference in reducing division in America Requirements - Experience in quantitative and mixed-methods research - Ability to sift through both small and large datasets - Comfort with navigating complex data sets (e.g., in Excel and R) - Experience designing and programming surveys (e.g., via tools like Qualtrics, Google Forms) - Experience conducting quantitative data processing and analysis (e.g., in Excel, R, Python) - Experience conducting segmentation analyses of survey data - Ability to build data dashboards - Can craft compelling data visuals (e.g., in R, Flourish, Canva, PowerPoint) - Experience with social media analysis or social listening - Experience conducting message testing research - Knowledge of AI tools for research analyses Benefits - Hourly rate of $60 per hour Company Description More in Common’s mission is to understand the forces driving us apart, find common ground, and help bring Americans together to tackle our shared challenges. We work with leaders across fields and across the ideological spectrum to support effective problem-solving, strengthen democratic institutions, and better navigate the dynamics of a polarized society. More in Common US works alongside teams in other major democracies. Globally, More in Common is comprised of a team of more than 70 people working in national offices in the US, UK, Germany, France, Poland, Spain, and Brazil. Our work is built on More in Common’s unique audience and opinion research, grounded in social psychology and political science. We promote a better understanding of Americans’ perspectives, providing fresh insights about not just what Americans think, but why. We engage with hundreds of organizations and leaders across sectors—including community groups, government, media, business, philanthropy, corporations, and faith communities—on a range of public issues.

Role Description The Institute for Health Metrics and Evaluation (IHME) has an outstanding opportunity for a Research Scientist to join their Reproductive, Genitourinary and Digestive (RGUD) disease estimation team. Reporting to the Acting Assistant Professor, the Research Scientist is responsible for driving high-impact global health research at IHME, analyzing quantitative data across causes of death, epidemiology, and social determinants to produce key estimates that inform global health policy. This role involves: - Leading research design - Mentoring junior staff - Contributing to peer-reviewed publications - Managing multiple projects in a collaborative environment The ideal candidate is a motivated, deadline-driven researcher ready to advance their career by translating cutting-edge scientific advances into meaningful global health insights. Our office is located in Seattle, Washington at the Hans Rosling Center for Population Health at the University of Washington. This position is eligible to work fully remote in the US; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time as agreed upon between employee and supervisor. Qualifications - Master’s degree in public health, epidemiology, statistics, biostatistics, math, economics, quantitative social sciences, or related discipline plus four years' related experience. - Growing peer network where sought out as having solid command of engineering/technical areas, a given disease, risk, key indicator, relevant methodological area, and the related data sources and scientific underpinnings. - Excellent analytic, critical thinking, and quantitative skills. - Results- and detail-oriented individual who can initiate and complete tasks under tight deadlines and changing priorities both independently and in a team environment. Flexibility with hours and workload is key. - Experience devising and executing statistical modeling techniques. - Demonstrated ability to quickly recognize problems in results and identify root causes in data, methods, and code. - Ease in designing, executing, and troubleshooting code in R. - Excellent written and oral communication skills required, including track record of success in co-authorship on multiple scientific papers, presenting results, and representing research at meetings. - Demonstrated ability to contribute to and sustain collaborations with external research teams. - Experience in working with large data sets, including devising strategies for reliable data management for large data sets, computationally efficient modeling techniques to use such data sets, and critical evaluation of highly multidimensional model outputs that result from such work. - Ability to work both independently and in collaboration with a team. - A long-term interest in a research scientist position contributing to the overall mission of our research. Requirements - MD or PhD in public health, epidemiology, statistics, biostatistics, math, economics, or quantitative social sciences plus two years’ experience preferred. - Experience with hepatic or other digestive disease epidemiology strongly desired. - Experience with endocrine, metabolic, or genitourinary disease epidemiology also somewhat desirable. - Expertise in implementing statistical models in a cluster environment to conduct analyses of large datasets and produce large numbers of estimates. - Experience applying rigorous approaches to model selection, testing, vetting and visualization. - Experience with machine learning, data mining, and analytic techniques. - Experience mentoring and developing junior employees on soft and technical skills. - Experience with project management methods. - Peer-reviewed publication record. Benefits - Pay Range Minimum: $110,052.00 annual - Pay Range Maximum: $137,460.00 annual - For information about benefits for this position, visit here . Company Description The Institute for Health Metrics and Evaluation (IHME) is an independent research organization at the University of Washington (UW). Its mission is to deliver to the world timely, relevant, and scientifically valid evidence to improve health policy and practice. IHME carries out its mission through a range of projects within different research areas including: - Global Burden of Diseases (GBD), Injuries, and Risk Factors - Future Health Scenarios - Cost Effectiveness and Efficiency - Resource Tracking - Impact Evaluations The Reproductive, Genitourinary and Digestive (RGUD) disease estimation team maintains and advances quantitative understanding of the health impacts, levels and trends of digestive diseases (including liver conditions – cirrhosis, hepatitis, and non-alcoholic fatty liver disease), gynecological and urinary disorders, sexually transmitted infections, and maternal disorders, and a subset of endocrine, metabolic, blood and immune disorders.

• Own post-training strategy for model development • Develop novel algorithms that improve model reliability, controllability, and alignment • Design and run experiments that shape model behavior, robustness, and reasoning quality • Manage, mentor, and grow a team of AI scientists

Role Description An Applied Scientist has a masters or PhD and is able to work with complex big data across multiple databases and sources, stitching together a cleaner version of data that is the foundation for analysis. Often times, Applied Scientists have to understand and research the intricacies of the data itself before using it to answer broader questions. More advanced coding and machine learning tools are usually required. Applied Scientists and Economists sometimes have to work together on a project, as their skill sets are complimentary. On occasion, Applied Scientists will also write research briefs, but more often than not they focus on methodology. About the role: - Design and evaluate statistical, econometric, and machine learning methods for forecasting problems. - Build backtesting and validation frameworks to assess forecast accuracy, stability, and downstream forecast impact. - Own the end‑to‑end modeling lifecycle, including scoping, feature engineering, model development, experimentation, deployment, monitoring, and model explainability. - Translate forecasts into clear insights and recommendations for senior leadership, helping stakeholders understand drivers, uncertainty, and trade‑offs that guide Zillow’s strategy. - Quantify uncertainty and clearly communicate model confidence, limitations, and trade-offs to technical and non-technical audiences. - Partner cross‑functionally with finance, product, engineering, marketing, and operations to scale and improve forecasting capabilities across Zillow. - Improve and contribute to shared forecasting tools, data pipelines, and processes used across the company. - Collaborate with other applied scientists and data scientists to develop novel solutions to real estate and business problems. This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions. In addition to a competitive base pay, employees in this role are eligible for incentive compensation subject to applicable laws and relevant Zillow policies. Actual amounts will vary depending on experience, performance and location. Qualifications - Advanced degree (PhD or Masters) in Economics, Statistics, Operations Research, Data Science, Computer Science, Econometrics, Mathematics, or a related quantitative discipline or a related quantitative discipline with 3+ years of experiences in professional applied scientist roles. - Strong experience with time-series forecasting, nowcasting, econometrics, or related quantitative modeling techniques. - Strength in data engineering principles to help envision efficient data solutions at scale. - Experience explaining complex models and analytical concepts to stakeholders with non-technical backgrounds using clear takeaways and practical business framing. - Experience building applied statistical or machine learning models that support real business decisions in production settings. - Proficient in Python and SQL for data analysis, model development, validation, and deployment. - Comfortable working with incomplete, delayed, or noisy real-world data and designing robust estimation strategies. Benefits - Competitive base pay. - Eligibility for incentive compensation subject to applicable laws and relevant Zillow policies. Company Description At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., Zillow helps millions of customers navigate buying, selling, financing, and renting with greater ease and confidence. Our teams in India play a critical role in building and scaling the technology, products, and operations that power this experience. - Zillow is honored to be recognized among the best workplaces in the U.S. - Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025. - Included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow. - Equal opportunity employer committed to fostering an inclusive, innovative environment.