About the company
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible. Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.
Job Summary
You Will
📍Establish subject-matter expertise in payment rails, focusing on cards (pre-paid, debit, credit, etc.) and bank rails (wire, ACH, direct deposit, etc.) 📍Influence product roadmaps and guide the Financial Operations (FinOps) team to navigate through product opportunities and problem ambiguities. 📍Build “soup to nuts” data products, taking raw eventing data from engineering teams and turning into actionable analyses and ML models. 📍Partner with Engineering and Operations leadership to drive a culture of data-driven financial impact. 📍Expand your influence in the Block Data Science community by developing and evangelizing data solutions to improve analytics insightfulness and actionability.
You Have
📍12+ years of related experience (data science, preferably in payment analytics, chargebacks, or related fields) with Bachelor's degree; or 8 years and a Master’s degree; or a PhD with 5 years experience; or equivalent experience 📍At least a bachelor's degree in a technical field such as Engineering, Physics, mathematics, computer science, etc. 📍Experience working on ambiguous problems with high business impact and resolving complex issues in innovative and efficient ways. 📍Expertise in hypothesis testing and causal inference. 📍A strong understanding and willingness to be hands-on in building data pipelines and architecture. 📍Ability to build strong relationships with cross-functional stakeholders, clearly communicating findings and influencing product designs. 📍Advanced proficiency with data, analytics, and visualization technologies (we use SQL, Looker, and Python).
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