Aug 2023 – Jul 2025 · 1 yr 11 mos · Bengaluru, Karnataka, India · On-site

Feb 2023 – Jul 2023 · 5 mos · Bengaluru, Karnataka, India · On-site

• Developed and maintained robust data pipelines using PostgreSQL at an early-stage climate startup, ensuring efficient fetching and manipulation of large datasets.
• Orchestrated complex workflows and scheduled data processing tasks with Apache Airflow, deployed data services on AWS using FastAPI, Kafka, and Postman for seamless integration.
• Contributed to database administration using pgAdmin, implemented pandas and numpy for efficient data manipulation and analysis in Python scripts for ETL processes, ensuring data quality and integrity

Jun 2022 – Jun 2023 · 1 yr

Jul 2021 – Jun 2022 · 11 mos

• Became part of the core team and managed club activities along with mentoring in the Machine Learning domain.

Nov 2020 – Jul 2021 · 8 mos

• Became coordinator and assisted in the club activities like workshops, content writing, etc. Kept on exploring more about the AI field like Computer Vision, NLP, Data Science, etc., and participated in hackathons.

Sep 2019 – Nov 2020 · 1 yr 2 mos

• Joined the Machine Learning domain and became a member of Innogeeks. I got to learn Python, data analysis/visualisations, etc. and worked on some basic ML projects.

Jun 2022 – Aug 2022 · 2 mos · Coventry, England, United Kingdom · On-site

• Got selected as one of the 15 fellows all over the world to participate in the DSSG Fellowship.
• Worked with Buckinghamshire Council & EY Foundation to predict the students at high risk of being
• NEET(Not in Education, Employment or Training) using Data Science techniques.
• We presented the project at the Shard, London in the final week of the fellowship. We also presented our project at the Learning & Doing Data for Good(LDDG) conference at the University of Washington.

Jun 2021 – Sep 2021 · 3 mos · Remote

• I worked in a team under the supervision of Prof. Setareh Rafatirad. I worked on supporting an application that analyzes housing data and provides price and rent estimates using machine learning models such as Random Forest and CNN. I collected valuable data and created reports. I also analyzed trends and gave presentations using data analysis to improve the business plan for the application. I also worked on fixing bugs of mobile applications in Android Studio.

Jan 2021 – Jun 2023 · 2 yrs 5 mos

• I am a β-MLSA (Microsoft Learn Student Ambassador). I get to connect and work on projects with other MLSAs worldwide. Also, host and attend several technical events.

Nov 2020 – Jan 2021 · 2 mos · Remote

• Used Photoshop to produce quality content. I was responsible for daily design and frequently added graphic elements.

Apr 2020 – May 2020 · 1 mo · Remote

• Wrote tutorials and technical posts on Python, OpenCV, Machine Learning, and many more.