Aditya Joshi
Vice President at Citi
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolAditya Joshi is a seasoned technology leader with 11 years of experience bridging capital markets and life insurance domains, now serving as Vice President at Citi. He combines deep backend expertise—Oracle PL/SQL, Sybase ASE/IQ, Python, and UNIX/Linux scripting—with proven delivery and people leadership, having led teams of 25–30 across multi-location agile projects. His career includes hands-on migration and performance work (Sybase→MS SQL, RHEL, Control‑M) and end-to-end ETL and automation efforts that improved scalability for regulatory reporting systems. An active contributor to open-source sustainability tooling, he implemented core CO2 tracking components and refactored modular code in the popular codecarbon project, reflecting interest in environmentally-aware ML engineering. Comfortable translating complex business requirements into robust, auditable systems, he also brings practical teaching experience from earlier academic roles. Based in Toronto, he blends operational rigor with a curiosity for ML and sustainable computing that goes beyond his domain-focused portfolio.
11 years of coding experience
12 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University of Mumbai
English, Hindi, Gujarati, Marathi
Stackoverflow
11reputation
6kreached
1answer
1question
Github Skills (13)
machine-learning10
trainings10
python10
modeling10
testing9
tensorflow9
keras9
scikit-learn8
scikit8
apscheduler7
documentation7
algorithm6
typedef6
Programming languages (5)
Github contributions (5)
mlco2/codecarbon
Jun 2020 - Nov 2020
Track emissions from Compute and recommend ways to reduce their impact on the environment.
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 21 commits, 8 PRs in 5 months
Contributions summary:Aditya primarily contributed to the codebase of a project focused on tracking and reducing emissions. Their work included implementing and integrating the core `CO2Tracker` and `OfflineCO2Tracker` classes, which are central to the project's functionality. They also created examples for hyperparameter tuning with `kerastuner` and `sklearn`, demonstrating expertise in model training and experimentation, and added unit tests to ensure robustness. The user also focused on code extraction and refactoring, improving modularity.
pythondata-scienceemissionscarbon-emissionsrecommend
adijo/smart-contract-engineer-challenges
Mar 2022 - Mar 2022
Contributions:24 commits, 19 pushes, 1 branch in 9 days
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