Srikanth Keshav Email & Phone Number | With 12+ years of experience in data science and analytics, I have a proven track record of driving product growth and business outcomes by surfacing anomalies and providing business critical recommendations. As a Manager of Data Analytics at Meta, I lead a team of data scientists and analysts who work on detecting and enforcing on financial and payments abuse across Meta's family of applications. I leverage machine learning models, heuristics based rules, and experimentation methodology to detect, measure, and enforce on bad actors in a way that balances the effect on good users. I am passionate about creating impact through others, empowering people to execute against their priorities, and collaborating with partners on shared goals and responsibilities. I have extensive experience in hiring, coaching, and managing data scientists and analysts, as well as partnering with engineering and product teams to help build robust decision recommendation systems that optimize for anomaly detection and good user experiences.

Srikanth Keshav

With 12+ years of experience in data science and analytics, I have a proven track record of driving...
Austin, Texas, United States

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Srikanth Keshav’s Email s.keshav@fb.com

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Srikanth Keshav’s Location Austin, Texas, United States

Srikanth Keshav’s Current Industry Meta

Srikanth Keshav’s Prior Industry Expedia | Deloitte | Sonus Networks

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Manager, Marketing Analytics

2015-05-01 00:00:00 - 2018-01-01 00:00:00

Senior Data Analytics Associate

2013-01-01 00:00:00 - 2015-01-01 00:00:00

Data Analyst Intern

2009-01-01 00:00:00 - 2010-01-01 00:00:00

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Srikanth Keshav is a With 12+ years of experience in data science and analytics, I have a proven track record of driving product growth and business outcomes by surfacing anomalies and providing business critical recommendations. As a Manager of Data Analytics at Meta, I lead a team of data scientists and analysts who work on detecting and enforcing on financial and payments abuse across Meta's family of applications. I leverage machine learning models, heuristics based rules, and experimentation methodology to detect, measure, and enforce on bad actors in a way that balances the effect on good users. I am passionate about creating impact through others, empowering people to execute against their priorities, and collaborating with partners on shared goals and responsibilities. I have extensive experience in hiring, coaching, and managing data scientists and analysts, as well as partnering with engineering and product teams to help build robust decision recommendation systems that optimize for anomaly detection and good user experiences.