Elizabeth Eardley, PhD
Verified Expert in Engineering
Data Scientist and Machine Learning Developer
Berlin, Germany
Toptal member since February 23, 2022
Elizabeth is a versatile data scientist, combining a strong scientific background from postdoctoral research with six years of industry experience, including Booking.com and Skyscanner. She excels at applying scientific techniques to data to support and automate decision-making, optimize products, and uncover actionable insights. Elizabeth has conducted extensive A/B testing and built and scaled multiple online experimentation platforms and optimization programs.
Portfolio
Experience
- Statistics - 11 years
- Data Science - 11 years
- Python - 11 years
- Data Analysis - 10 years
- Hypothesis Testing - 10 years
- SQL - 10 years
- A/B Testing - 6 years
- Experimental Design - 6 years
Work Experience
Head of Data Science
US-based SaaS Startup
- Led engineering and design teams to deliver projects from discovery and design through implementation and release. Projects included false discovery rate control, multiformat results and reporting exports, and automatic degradation detection.
- Researched and designed new statistical algorithms and causal inference methods. Served as the lead inventor on the US patent for a statistical technique to accurately detect poor-performing software changes as quickly as possible.
- Provided client consultations and support in experimental design. Led internal training sessions and initiatives to accelerate a culture of data-driven decision-making.
- Delivered a wide variety of ad hoc data science support across all departments, including analyses, insights, and reporting.
Senior Data Scientist
Skyscanner
- Led the research and development of numerous extensions and improvements to the internal experimentation platform, including false discovery rate controls, guided power analyses, and in-depth reporting on experiment results.
- Supported the design, implementation, and analyses of dozens of A/B tests across product, engineering, and marketing.
- Ran internal training sessions and initiatives to grow the internal culture of data-driven decision-making and scale experimentation across the organization.
Data Scientist
Booking.com
- Developed productionized machine learning models, such as predicting the intent of a visitor to serve an optimal version of the product for the visitor's needs and preferences.
- Designed, implemented, and analyzed A/B tests, driving numerous product decisions and influencing the long-term plans of multiple product engineering teams.
- Measured the incremental value of loyalty programs and membership types using quasi-experimentation techniques like difference-in-differences, cohort analysis, regression discontinuity models, propensity score matching, and instrumental variables.
Postdoctoral Researcher
University of St Andrews
- Applied modeling and machine learning techniques (classification and regression) to large numerical simulations of our universe to predict unobservable features of real galaxies.
- Developed a novel method to extract valuable signals from the noisy and imperfect data of observed galaxy spectra.
- Found statistically significant correlations between dark matter properties and their geometric environments. The results were published in peer-reviewed scientific journals.
Project History
Analysis of the Effect of the Randomization Unit in Online Experiments
Published Work
https://scholar.google.com/citations?hl=en&user=7rPSEysAAAAJEducation
PhD in Astrophysics
University of Edinburgh - Edinburgh, Scotland, UK
Master's Degree in Physics
University of Oxford - Oxford, England, UK
Skills
Tools
Slack, Git, Jupyter, IntelliJ IDEA, Jira, Google Analytics
Languages
SQL, Python, Snowflake, R, Fortran, Java
Frameworks
Hadoop
Platforms
Databricks, MacOS, Mixpanel
Storage
Redshift, Apache Hive
Other
Statistics, Data Analysis, Data Inference, Hypothesis Testing, Experimental Design, A/B Testing, Data Science, Mathematics, Physics, Mode Analytics, Segment, Computational Physics, Statistical Methods, Scientific Computing, Technical Writing, Research, Machine Learning, Data Visualization, Reporting, Product Management, Product Roadmaps, Customer Support, Public Speaking, US Patent Process, Causal Inference, Bayesian Inference & Modeling, Data Communication, Classification Algorithms, Linear Regression, Statistical Significance, Leadership
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