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Sr. Scientist, AI for Databases | AWS | UC Berkeley
I am a senior applied scientist, part of AWS Learned Systems Group (LSG) at Amazon led by Prof. Tim Kraska. I work at the intersection of machine learning and database systems. My research aims at building autonomous database systems and warehouses— systems that autoscale, self-heal, and self-optimize at scale. Some of my research has been deployed over years at scale in database services offered by Amazon like RDS Aurora, MySQL, PostgreSQL, Oracle and data warehouses like Amazon Redshift. Lately, I am involved in building SoTA specialised AWS-native LLM agents for various downstream tasks, like SRE agent for Databases (PANDA) and Data Science Agent for Amazon SageMaker. My personal webpage: svikramank.github.io
University of California, Berkeley
Master's degree, Artificial Intelligence
August 1, 2018 – May 1, 2020
University of Mumbai
Bachelor's degree, Computer Engineering
June 1, 2012 – May 1, 2016
Amazon Web Services (AWS)
Sr. Applied Scientist
June 1, 2020 – Present
San Francisco Bay Area
Ericsson
ML Researcher
May 1, 2019 – May 1, 2020
Santa Clara, California, United States
University of California, Berkeley
Graduate Student Researcher
August 1, 2018 – May 1, 2020
Berkeley, California, United States
MIT Media Lab
Researcher
July 1, 2017 – April 1, 2018
Boston, Massachusetts, United States
Meta
Machine Learning Engineer
October 1, 2016 – July 1, 2017
Mumbai, Maharashtra, India
Indian Institute of Science (IISc)
Research Fellow
June 1, 2014 – September 1, 2014
Notemybook Pvt Ltd
Co-Founder and CEO
January 1, 2014 – October 1, 2016
Mumbai, Maharashtra, India
Cultural Fit Analysis
The candidate's diverse experience across research, industry, and entrepreneurship, including roles at top-tier companies and academic institutions, suggests adaptability and a broad perspective. However, the target role is 'Data Analyst', which is a significant shift from their 'Sr. Applied Scientist' and 'ML Engineer' background. While they have strong data-related skills, the direct alignment with a pure 'Data Analyst' role, which often focuses more on reporting, dashboarding, and business intelligence rather than advanced ML/AI model development, is not explicitly demonstrated. This might indicate a potential mismatch in day-to-day responsibilities and expectations for a typical Data Analyst role, though their analytical capabilities are undoubtedly high.
Soft Skills & Operational Fit
The candidate's entrepreneurial background and leadership roles suggest strong initiative, problem-solving, and strategic thinking. Experience in research and applied science indicates a methodical approach to complex problems. The descriptions, while concise, highlight significant achievements and responsibilities, implying effective communication of technical concepts.