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Automating data synthesis to advance data privacy.

Jobs at Tonic

Big data has a big problem: we’re using it wrong. From unintended data breaches to undisguised invasions of privacy, companies are struggling to manage their data responsibly. We know because we’ve been there, and it inspired us to redirect our careers in data analytics and focus on the bigger challenge that truly stands to unlock data’s potential: data synthesis.

Our goal at Tonic is to make it easier for organizations to use their data effectively while doing right by their customers, employees, and business partners. It’s a complex endeavor requiring solutions that work as well in the context of finance as they do in healthcare as they do in edtech. We’re asking and answering questions of database subsetting, masking, scaling, anonymization, differential privacy, and de novo synthesis. How do you maintain referential integrity across 100s of tables when you scale a relational dataset 1000x? How do you performantly subset a petabyte database? How do you implement differential privacy so that an end user doesn't have to read four academic papers to understand how it works? And how do you ensure that the data you're generating can't be traced back to a real person? The tools we're building in response are redefining the way teams access, share, and use the data their work depends on.

The world needs quality data. Thanks to Tonic, quality data no longer means real data. Join us, and help us build a better way to work with today’s most valuable resource.