Develops, interprets, and implements statistical, financial, and accounting concepts and quantitative techniques to support credit risk modeling, financial forecasting, model monitoring, and reporting.
Responsibilities
Apply statistical theory, econometric methods, and quantitative techniques to collect, organize, validate, interpret, and summarize numerical and text data to provide usable information.
Interpret quantitative data and design statistical models for researching problems or questions.
Perform data analysis using statistical programming software such as Python, R, or SAS, with emphasis on accuracy, reproducibility, data quality, and effective analytical controls.
Analyze and interpret data to identify trends, patterns, anomalies, and emerging risks that may affect performance, model results, or estimates.
Develop and maintain analytical programs, reusable scripts, data validation routines, and automated workflows that improve the efficiency and consistency of quantitative processes.
Requirements
Bachelor's degree in Statistics, Mathematics, Mathematics, or Economics with a strong quantitative concentration, Data Science, or another closely related quantitative discipline.
Master's degree in Statistics, Mathematics, Economics, or Data Science
Support causal inference and marketplace measurement work for Expedia Group's Economics and Experimentation Science team.
Locations (2)
Seattle, Washington, United States
Austin, Texas, United States
Compensation
The total cash range for this position in Seattle is $119,000.00 to $166,500.00. The total cash range for this position in Austin is $119,000.00 to $166,500.00.
Responsibilities
Build econometric models (panel data methods, DiD, RDD, IV) to help measure elasticity, changes in supplier behavior, and customer lifetime value in the presence of endogeneity, simultaneity, and platform dynamics
Support the development of long-term impact measurement approaches, helping the team move beyond short-term experiment metrics toward quantifying sustained effects on customer retention, partner engagement, and marketplace equilibrium
Assist in designing and executing causal measurement frameworks for marketplace interventions, including geo experiments, difference-in-differences, synthetic controls, and instrumental variable approaches
Lead the technical implementation and development of economic forecasting models, including city, regional, and hyperlocal applications
Ensure that Oxford Economics’ city forecasting models and analytical pipelines are technically robust, scalable, and aligned with the latest methodological developments
Present research findings to internal teams, clients, and stakeholders with clear, actionable recommendations
Line-manage and lead a small team of economists and data scientists
Design, code, implement, and maintain quantitative models to assess economic performance, spatial disparities, and the impact of geographic factors on economic activities
Requirements
Strong academic education in economics, geography, data science, or a related discipline
Nice to have: experience developing forecasting models for city, regional, or small-area applications
Nice to have: experience with spatial econometrics
Nice to have: experience leveraging machine learning techniques for classification and regression
The Senior Research Scientist applies statistical, epidemiologic, and causal inference methods to large, complex healthcare datasets to evaluate clinical program performance, identify drivers of outcomes, and inform strategic and operational decisions.
Compensation
$104,000 - $143,000 per year
Responsibilities
Design and execute rigorous outcomes studies to evaluate the clinical, utilization, and financial performance of clinical programs using observational and experimental methods.
Apply causal inference, epidemiologic, and statistical methods to estimate program impact and generate credible evidence for decision-making.
Conduct deep-dive analyses using medical and pharmacy claims, enrollment, and operational data to identify key performance drivers, diagnose performance gaps, and uncover opportunities for improvement.
Translate broad or ambiguous clinical and business questions into well-defined analytical questions, hypotheses, and study designs.
Partner with clinical, operational, financial, and business stakeholders to translate analytical insights into recommendations that inform clinical strategy, program design, contracting, and performance improvement.
The Research Scientist 2 applies statistical, epidemiologic, and analytical methods to healthcare data to evaluate clinical program performance, understand drivers of outcomes, and support clinical and business decision-making.
Compensation
$78,400 - $107,800 per year
Responsibilities
Design and execute outcomes studies to evaluate the clinical, utilization, and financial performance of clinical programs using observational and experimental methods.
Apply causal inference, epidemiologic, and statistical methods to estimate program impact and generate credible evidence for decision-making.
Conduct deep-dive analyses using medical and pharmacy claims, enrollment, and operational data to identify key performance drivers, diagnose performance gaps, and uncover opportunities for improvement.
Translate clinical and business questions into clearly defined analytical questions and hypotheses, partnering with senior scientists as needed on more complex study designs and methodologies.
Partner with clinical, operational, financial, and business stakeholders to translate analytical insights into recommendations that inform clinical strategy, program design, contracting, and performance improvement.
Partner with ML teams to help integrate causal inference into production systems, supporting ranking algorithms, pricing optimization, and recommendation engines with econometrically validated insights
Translate econometric findings into clear, well-organized analysis and visualizations that support product decisions, and present results to stakeholders with clarity
Requirements
Master's degree in Economics, Applied Economics, Econometrics, Statistics, or a related quantitative field
Bachelor's degree with equivalent related professional experience
Nice to have: PhD in Economics, Applied Economics, Econometrics, Statistics
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