Chethan Radhakrishna
Data Scientist
Mysuru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolChethan Radhakrishna is a data scientist and full-stack engineer with nine years of experience blending web development and data analytics to make complex project metrics actionable. He has built real-time dashboards and automated CI/CD deployments at Bosch Engineering, turning SPLUNK and multi-source lifecycle data into management-grade visualizations used across international teams. Prior roles span full-stack work with React/Redux, Node.js event sourcing, and cloud deployments on AWS, giving him end-to-end delivery fluency from APIs to production pipelines. His academic background in Data and Knowledge Engineering complements hands-on experience analyzing requirement-management toolchains and sprint data to surface process improvements. Curious by nature, he pairs a visual-first approach to data with an engineer’s attention to automation and reproducible dashboards. Based in Mysuru, he brings a pragmatic, observability-driven mindset to bridging software development and data-driven decision making.
9 years of coding experience
5 years of employment as a software developer
Master's degree, Data and Knowledge Engineering, 2.2, Master's degree, Data and Knowledge Engineering, 2.2 at Otto-von-Guericke University MagdeburgB.E in Computer Science and Engineering, Computer Science, CGPA: 7.68, B.E in Computer Science and Engineering, Computer Science, CGPA: 7.68 at Vidya Vardhaka College of Engineering
English, Hindi, Kannada, German
Github Skills (26)
kinect-v210
kinect-sdk10
kinect10
multer-storage7
multer5
mongoose5
deep-learning3
crud3
mongodb3
pytorch3
bootstrap3
expressjs3
css3
nodejs3
interpretable-machine-learning2
Programming languages (7)
Github contributions (5)
chethanMysore/UnSupDFC
Apr 2022 - Nov 2022
Contributions:48 commits, 45 pushes, 3 branches in 7 months
ravi22342/DS6
Jan 2022 - Jan 2024
DS6: Deformation-aware learning for small vesselsegmentation with small, imperfectly labeled dataset
Contributions:134 pushes, 15 branches in 2 years
deep-learningpytorchdatasetdeformation
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