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Data Scientist - Analytics






San Francisco, CA, US


At Plaid, we believe that the way consumers and businesses interact with their finances will drastically improve in the next few years. Our goal is to build tools and products to enable developers to create this next generation of financial services applications. Today, hundreds of companies such as Venmo, Square, and Coinbase rely on Plaid to integrate with banks and the financial system.

Making data driven decisions is key to Plaid's culture. To support that, we need a data science team that can build and maintain core data sets, metrics, and dashboards. In the product development process. we rely on experimentation heavily, so that we can quantify the impact of new features and products and rapidly iterate. We also provide tools and guidance to teams across engineering, product, and business to help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively.

Our data science culture is IC-driven -- we favor bottom-up ideation and empowerment of our incredibly talented team. We are looking for data scientists who are motivated by creating impact for our consumers and customers, growing together as a team, shipping the MVP, and leaving things better than we found them.

What excites you

        Designing and interpreting experiments to measure the impact of new features on Plaid's website and mobile SDKs
        Defining core data sets and schemas, as well as visualizing and tracking key metrics
        Running impactful inferential analyses and data investigations to identify recurring patterns, root causes, and propose actionable product solutions
        Communicating analyses and data-backed recommendations to stakeholders
        Championing a data-first approach toward decision-making across the entire organization
        Mentoring and growing other data scientists into senior roles and establishing a culture of statistical excellence

What excites us

        5+ years of industry experience in a Product Data Science role
        Deep understanding of various statistical techniques and experimentation analysis workflows
        Strong familiarity with SQL, data visualization tools, and working knowledge of Python
        Data engineering experience and data pipeline tooling (e.g. Airflow, Redshift) experience is a plus
        Bachelor's degree or equivalent work experience in Computer Science, Mathematics, Statistics, Operations Research, Economics, or a closely related field

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