Full Stack Data Scientist

Decisions are at the foundation of every Bounce experience. As a Full Stack Data Scientist you will work in a dynamic environment, embracing moving quickly to ensure data is at the heart of Bounce's products and decision-making. The focus of this position will be on interacting with various cross-functional teams and stakeholders at Bounce.

You will be performing analysis and creating models that help each Bounce team achieve our goals. You will also help analyze overall business trends, look for and explore key insights. You should have a deep understanding of Machine Learning, Data Analytics, and Visualization. You will play a critical role in the success of Bounce!

Where you come in..

  • Partner with cross-functional teams and respective stakeholders to translate analytical insights into action
  • Leverage data to track key operational metrics in dashboards, develop an expansion strategy, and forecast capacity
  • Establish operational KPIs and build frameworks to monitor the performance of store partners
  • Help develop and maintain our analytics pipelines
  • Advocate for data and data-driven decisions
  • Improve our Data Focused Agentic Layer
  • Be an owner, taking a personal stake in the success of the product and the team

Requirements

  • Experience with data visualization and orchestration tools such as Amplitude, Tableau, Hex, and Airflow
  • Comfortable with data warehousing concepts, big data technologies, and analytics platforms
  • Knowledge of Agentic Tooling: Claude, Jules, or Codex are a must
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
  • Avid learner and practical problem solver
  • Ability to provide strategic guidance to senior leadership based on data-driven insights
  • Experience supporting product teams by developing A/B testing tooling and underlying data
  • Ability to implement sophisticated attribution models and customer segmentation frameworks to optimize marketing ROI and personalization capabilities
  • Ability to build modern, internal self-serve data capabilities to support business operations
  • Experience implementing AI and machine learning solutions at scale
  • Ability to manage big data infrastructures and cloud-based analytics platforms
  • Experience driving observability and data quality frameworks to ensure stakeholder trust in metrics

See also

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