Geoff Rollins
Data Scientist | Analytics Engineer | Biophysics PhD
Professional Summary
- Data Scientist with strong quantitative background that spans data science, analytics engineering, and physics
- 6+ years experience working with petascale data in a fast-paced tech startup environment with extensive remote experience
- 10+ yrs experience with Python; 6+ yrs experience with R and SQL
- Delivers end-to-end data science projects: from measurement strategy and statistical inference to data pipelines to dashboarding to deep-dive reports
- Passionate about refactoring legacy code to mitigate technical debt, guided by tests
- Effective communicator – experienced in writing and presenting reports to both business and technical audiences
Work History
Senior Data Scientist | Atlassian (Trello team)
- Worked closely with PMs on measurement goals and strategy for new feature launches
- Applied causal methods to quantify the impact of an important feature launch on monetization when a/b testing wasn’t available
- Analytics engineering: built dozens of data pipelines and dashboards for analysis and reporting using Databricks and Mode
Software Engineer in Test | DataStax
- Tested Apache Cassandra at scale using Python, Jenkins and in-house tools
- Built custom dashboards and data pipelines in Python and R to make it easy for PM and dev teams to monitor test results and catch regressions early
- Safely refactored and added new functionality to a legacy ETL tool for extracting data from Jenkins and loading results into test tracking platform
Data Architect | Dropbox
- Focused on analytics engineering: refactored and optimized key data pipelines in Hive and Luigi to stabilize and speed up operational reporting for Customer Analytics team, eliminating significant technical debt along the way
- Built dashboards using in-house Tableau-like platform to track Dropbox Help Center traffic
Data Scientist | Dropbox
- Led the development of a new customer satisfaction survey that influenced overall company strategy. My work covered all phases of the project: questionnaire design, population sampling, statistical analysis, and presentation of findings and recommendations to diverse set of stakeholders
- Built predictive models of customer churn and worked with a cross-functional team to A/B test marketing campaigns to reduce churn; also built reporting pipelines and dashboards to track churn