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Plaid // democratizing financial services thru tech
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We believe the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools & infrastructure developers need to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo & SoFi, several of the Fortune 500, & many of the largest banks to make it easy for people to connect their financial accounts to the apps & services they want to use. Plaid's network covers 11,000 financial institutions across the US, Canada, UK & Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Salt Lake City, Washington D.C., London & Amsterdam.

Transactions, Investments, & Liabilities represent a handful of Plaid's core & most impactful products.
These products are Plaid's largest & most comprehensive set of data. We take in millions of messy raw transaction, investment, & loan data  from thousands of banks in unique formats, standardize them into a single structured schema, & then enrich them with both derived & inferred insights.
We employ a mix of traditional & machine learning techniques, & take pride in solving non-deterministic problems. The fruit of our labor is the FinTech industry default API for accessing users' transaction data, investment holdings data, & loan data. Not only does our work power Plaid's massive ecosystem of customers & partner banks, but also the entire range of our other product offerings.

 As a member of the LIT (Liabilities, Investments, Transactions) team, you'll collaborate with data scientists on novel ML solutions, Product Managers to build out our API, & engineers across the company on a range of projects & products. You'll have the opportunity to pick up multiple languages & technologies, you'll have the space to explore unsolved problems, & your work will impact millions of customers by bringing order to the chaotic world of financial data.
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