Responsibilities
- Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Inform, influence, support, and execute our product decisions and product launches.
- The Data Scientist Analytics role has work across the following four areas:
- Product Operations
- Forecasting and setting product team goals
- Designing and evaluating experiments
- Monitoring key product metrics, understanding root causes of changes in metrics
- Building and analyzing dashboards and reports
- Building key data sets to empower operational and exploratory analysis
- Evaluating and defining metrics
- Exploratory Analysis
- Proposing what to build in the next roadmap
- Understanding ecosystems, user behaviors, and long-term trends
- Identifying new levers to help move key metrics
- Building models of user behaviors for analysis or to power production systems
- Product Leadership
- Influencing product teams through presentation of data-based recommendations
- Communicating state of business, experiment results, etc. to product teams
- Spreading best practices to analytics and product teams
- Data Infrastructure
- Automating analyses and authoring pipelines via SQL and Python
- Product Operations
Minimum Qualifications
- 5+ years of experience doing quantitative analysis.
- BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field. Advanced degrees.
- Experience in SQL or other programming languages.
- Development experience in any scripting language (PHP, Python, Perl, etc.)
- Ability to communicate the results of analyses.
- Understanding of statistics (e.g., hypothesis testing, regressions).
- Experience manipulating data sets through statistical software (ex. R, SAS) or other methods.
Preferred Qualifications
- Experience with distributed computing (Hive/Hadoop)