
Shivnath Pradhan
@shivnathpradhan
Data Analyst focused on SQL and BI, with loan-lending and HR dashboards that surface actionable trends.
What I'm looking for
My Bank Loan Lending Analysis project turned 38K+ loan records into an end-to-end SQL pipeline and an interactive Power BI dashboard with KPI reporting.
For my HR Analytics Dashboard, I analyzed 1,470 employee records, identified a 16.12% attrition rate, and built a seven-sheet Tableau dashboard to explore attrition patterns.
At CoderOne, I led a four-member team developing ML and NLP pipelines, including a CNN that achieved 85%+ accuracy on the MNIST dataset. I also developed a text summarization model using Hugging Face BART/T5 and automated machine-learning workflows.
My Smart Procurement & Vendor Risk Management System used SAP RAP, CDS Views, and OData V4 to support vendor analytics and automated risk scoring. I’m seeking a Data Analyst role where I can use data to help drive business decisions.
Experience
Work history, roles, and key accomplishments
Data Annotation Intern
Macgence
Sep 2025 - Mar 2026 (6 months)
Annotated and labeled large-scale datasets to improve AI/ML model performance for text and image understanding. Maintained high data accuracy and consistency, enhancing overall dataset quality.
Data Science & Analytics Intern & Team Lead
CoderOne
Dec 2024 - Feb 2025 (2 months)
Led a team of 4 members to develop ML/NLP pipelines, achieving 85%+ accuracy using CNN on MNIST dataset. Developed a text summarization model using Hugging Face BART/T5 with data preprocessing and feature engineering.
Education
Degrees, certifications, and relevant coursework
Veer Surendra Sai University of Technology, Burla
Bachelor of Technology, Information Technology
2022 -
Grade: CGPA: 8.47
Pursuing Bachelor of Technology in Information Technology with a CGPA of 8.47.
Marwari +2 High School, Chakradharpur
Intermediate, Science
2020 - 2022
Grade: 91%
Completed Intermediate (Science) with 91% from JAC Board.
S S +2 High School, Sonua
Matriculation, General
2018 - 2020
Grade: 90.8%
Completed Matriculation with 90.8% from JAC Board.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
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