Job Description
The Cash App Data Science (DS) organization is growing and we are looking for a Data Scientist to join the team, embedded within our Sales and Account Management domain. You will be responsible for deriving valuable insights from our extremely unique datasets as well as developing models, forecasts, analyses, reports to help achieve merchant acquisition, retention, growth and profitability goals.
You will:
- Partner directly with the Cash App Sales & AM team, working closely with operations, strategy, engineers, account executives/managers and leads
- Analyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to key stakeholders
- Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand merchant behavior
- Design and analyze A/B experiments to evaluate the impact of changes we make to our operational processes and tools
- Work with engineers to log new, useful data sources as we evolve processes, tooling, and features
- Build, forecast, and report on metrics that drive strategy and facilitate decision making for key business initiatives
- Write code to effectively process, cleanse, and combine data sources in unique and useful ways, often resulting in curated ETL datasets that are easily used by the broader team
- Build and share data visualizations and self-serve dashboards for your partners
- Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis
Qualifications
You have:
- An appreciation for the connection between your work and the experience it delivers to customers. Previous exposure to or interest in marketplace platforms specially on the merchant side, would be great to have.
- A bachelor degree in statistics, data science, or similar STEM field with 8+ years of experience in a relevant role OR
- A graduate degree in statistics, data science, or similar STEM field with 6+ years of experience in a relevant role
- Advanced proficiency with SQL and data visualization tools (e.g. Looker, Tableau, etc)
- Experience with scripting and data analysis programming languages, such as Python or R
- Experience with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilities
Technologies we use and teach:
- SQL, Snowflake, etc.
- Python (Pandas, Numpy)
- Looker, Mode, Tableau, Prefect, Airflow
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