Block - Bay Area, CA

posted about 1 month ago

Full-time - Senior
Bay Area, CA
Publishing Industries

About the position

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 Data Scientist, you will play a critical role in accelerating Cash App's growth by creating and improving how we acquire new users onto the platform. 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 and explore new opportunities to enable Cash App to become the top provider of primary banking services to our customers.

Responsibilities

  • Own the Cash Lifecycle Marketing holdout review
  • Build models to optimize our marketing efforts to ensure our spend has the best possible ROI
  • Design and analyze A/B experiments to evaluate the impact of marketing campaigns we run
  • Support audience sizing and campaign results tracking
  • Analyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the Marketing product team and other key stakeholders
  • Partner directly with the Cash App Marketing org to influence their roadmap and define success metrics to understand the impact to business
  • Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior & segments
  • 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

Requirements

  • A degree in statistics, data science, or similar STEM field with 8-10+ years of experience in data science
  • Significant focus on acquisition marketing analytics and deep understanding of marketing funnel metrics, attribution models, and customer lifetime value (CLV) calculations
  • Expertise in causal inference methods (e.g., propensity score matching, synthetic control methods, instrumental variables)
  • Proficiency in statistical programming languages (e.g., Python, R) and data manipulation tools (e.g., SQL, Spark)
  • Proven ability to communicate complex analytical concepts to non-technical stakeholders

Nice-to-haves

  • Experience with SQL, Snowflake, etc.
  • Familiarity with Python (Pandas, Numpy)
  • Experience with Tableau, Airflow, Looker, Mode, Prefect

Benefits

  • Market-based pay
  • Flexible working environment
  • Inclusive workplace policies
  • Opportunities for professional development
  • Health and wellness benefits
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