ABOUT ME
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Suparna Chowdhury

Data Scientist

LinkedIn

I translate complex data into actionable insights, driving tangible business results. My expertise in machine learning, predictive modeling, and NLP empowers teams to make smarter, faster, data-driven decisions.

Whether it is building robust models in Python or crafting clear dashboards in Tableau, I bring a mix of technical depth and strategic focus — always aligning solutions with customer needs.

When I am not working with data, I enjoy playing the piano to relax and recharge. Known for blending adaptability with code (and the occasional chord), I am a collaborative problem-solver who transforms noise into clarity.

EDUCATION
University of South Alabama Logo

MS in Electrical Engineering

University of South Alabama, Alabama • July 2015

PUBLICATIONS

A reinforcement learning algorithm based technique for thermal energy management of a PEM fuel cell power plant

IEEE • December 2017

Efficient face recognition using local derivative pattern and shifted phase-encoded fringe-adjusted joint transform correlation

SPIE · April 2016

CERTIFICATIONS
IBM Data Science Professional Certificate

IBM Data Science Professional Certificate

IBM • January 2023

Fundamentals of Visualization with Tableau

Fundamentals of Visualization with Tableau

IBM • January 2023

Analytics in Action
Data Governance & Compliance Risk Dashboard

Data Governance & Compliance Risk Dashboard Project

Power BI dashboard project translating governance and compliance audit metrics into quantified business risk and financial exposure.

A SQL Project on Retail Sales, Retention, and Cohort Analysis

A real-world SQL retail analytics project to uncover sales trends, analyze customer retention through cohorts, and assess the impact of discounting.

Tableau Dynamic Zone Visibility Dashboards

Mastering Dynamic Zone Visibility in Tableau Design Patterns

A two-part technical article series on building clean and interactive Tableau dashboards with practical Dynamic Zone Visibility use cases.

Data Science Deep Dives

Decoding Urban Patterns: K-Means Clustering Analysis

This project segments 300 cities into distinct archetypes using unsupervised learning, feature engineering, and clustering techniques to inform urban planning decisions.

Predicting Loan Defaults: ML-Powered Risk Assessment

Built XGBoost classifier achieving 93% accuracy on 32K+ loans, identifying $77M in default risk through feature engineering and deployed insights via interactive Power BI dashboard.

Data Governance & Compliance Risk Dashboard Project

A risk-based data governance dashboard that converts compliance metrics into financial exposure and executive action priorities.

Areas of Interest

Machine Learning

Machine learning is a tool, not a buzzword—I love optimizing algorithms and solving real business problems.

Natural Language Processing

With NLP, I extract insights from messy text and turn human language into structured knowledge.

Data Visualization

Data speaks louder when visualized—I enjoy designing charts that drive decisions.

Statistical Analysis

I use statistical techniques to validate assumptions and guide decision-making with confidence.

SQL Database

SQL is my tool for organizing data, running efficient queries, and making sense of massive datasets.

Data Preprocessing

I treat data preprocessing as an art—refining raw data into clean, efficient structures for efficient analysis.