Sourav NandaSN
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Sourav Nanda


Backend developer proficient in software development as well as building and integrating REST APIs.


What I'm looking for

In my next role, I seek a dynamic, innovative environment where I can learn and grow. I value collaboration, continuous learning, and opportunities for professional development. I'm open to new challenges and diverse responsibilities and contributing to the organization's goals.

I am an experienced Backend developer, I have a strong track record of creating reliable, user-oriented applications. I take pride in my ability to build robust APIs, implement data validation procedures, and adhere to efficient coding practices. Moreover, my expertise extends to working with NoSQL databases, particularly MongoDB, and I am well-versed in utilizing MySQL in production environments. Throughout my career, I have also gained valuable experience in data analysis, having successfully worked on projects in diverse domains like Geothermal Power analysis and sports.

I have worked upon web applications primarily working in Django and have experience in ORM as well as authentication and security procedures.

In the realm of cloud computing, I am already familiar with AWS Lambda and actively expanding my knowledge to encompass other services, with a particular focus on S3, Beanstalk, and EC2. My commitment to continuous learning ensures that I can swiftly acquire a comprehensive understanding of these services through practical experience and diligent self-study.


Nextwealth logoNE

Automation Developer


Aug 2022 - Nov 2022 (3 months)

I created an enhanced workflow for LIDAR dataset labeling and error correction by developing a Windows OS app, complemented by a Django project for registration and administration. This automated workflow significantly boosted productivity for over 100 employees and optimized overall operations. The process underwent four major iterations, incorporating flexibility and received positive feedback.


Data Anlyst


Oct 2020 - Nov 2020 (1 month)

Utilized analytical techniques with Pandas and Numpy to analyze IPL datasets, extracting underlying patterns. Insights were drawn from visualizations using Matplotlib and Seaborn. Statistical significance tests, including p-value calculations, were conducted to assess the significance of findings. Created ML models for predicting outcomes of regular matches of T-20.

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