Job Description
The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day. As a Marketing Data Scientist, you will play a critical role in accelerating Cash App's growth by creating and improving how we measure the impact of all our marketing efforts.
In this role, you'll be embedded in our Marketing organization and work closely with quantitative finance, marketers, product management as well as other cross-functional partners to help us understand the incrementality of paid marketing initiatives at different network levels, create a validation plan for our mixed marketing model, and explore new opportunities to enable Cash App to become the top provider of primary banking services to our customers.
You will:
Build models to optimize our marketing efforts to ensure our spend has the best possible ROIDesign and analyze A/B experiments to evaluate the impact of marketing campaigns we launchAnalyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the Marketing product team and other key stakeholdersPartner directly with the Cash App Marketing org to influence their roadmap and define success metrics to understand the impact to businessApproach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior & segmentsBuild, forecast, and report on metrics that drive strategy and facilitate decision making for key business initiativesWrite 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 teamBuild and share data visualizations and self-serve dashboards for your partnersEffectively communicate your work with team leads and cross-functional stakeholders on a regular basisQualifications
A degree in statistics, data science, or similar STEM field with 7+ years of experience in a relevant roleAdvanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)Experience with scripting and data analysis programming languages, such as Python or RWorked extensively with Causal Inference techniques and off platform dataA knack for turning ambiguous problems into clear deliverables and actionable insights Gone deep with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilitiesExperience working with customer acquisition dataManaged relationships with external vendorsTechnologies we use and teach:
SQL, Snowflake, etc.Python (Pandas, Numpy)Tableau, Airflow, Looker, Mode, Prefect
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