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Sushma Thamatam

Data Analyst • India • github.com/••••• • drivetube.ai/•••••

Career Objective

Machine Learning Engineer experience in Java, C, MATLAB, SQL, and data processing. Processed 2GB of speech data using Java and Snowflake for classification modeling and analysis. Optimized MATLAB signal-processing algorithms in C, reducing execution time by 75%. Built Tableau and Power BI dashboards for model accuracy, fraud, revenue, and retention analysis. Used Git, SQL, and Snowflake to support data pipelines, analysis, and research workflows.

Education

Lakireddy Bali Reddy College of Engineering (JNTUK)
Bachlor of Technology in Electronics and Communication Engineering • 2022 – 2026

Technical Skills

Programming Language: Java,C,SQL
Databases: Snowflake
Version Control & Development Tools: Git,Jupyter Notebook
Data Analysis & Visualization: Tableau,Power BI
AI/ML Frameworks & Libraries: scikit-learn

Projects

E-commerce Sales and Customer Analytics
Tools Used: Snowflake, SQL, Power BI
  • Modelled a star schema in Snowflake for 12 months of orders, customers and products, enabling sub-second drill-down queries.
  • Cleaned duplicate and null records with Excel functions before bulk loading, improving data quality by 15 %.
  • Built interactive Power BI dashboards showcasing revenue trends and cohort retention that guided simulated pricing decisions.
Fraud Analytics Dashboard
Tools Used: Snowflake, SQL, Tableau
  • Aggregated 5 million transaction rows in Snowflake with window functions to flag anomalies based on spend velocity.
  • Designed Tableau visualisations that allowed users to filter fraud scores by region and card type in real time.
  • Benchmarked query performance and indexed high-activity tables, cutting dashboard load time from 9 s to 3 s.
Sleep Apnea Detection
Tools Used: MATLAB, C
  • Processed polysomnography signals in MATLAB to extract respiration and oxygen-saturation features for anomaly detection.
  • Converted feature-extraction algorithms to C for embedded deployment, reducing memory footprint by 60 %.
  • Evaluated detection accuracy on 50 patient records and achieved 88 % precision without hardware acceleration.
Speech Processing Using Machine Learning
Tools Used: Java, SQL, Tableau
  • Implemented Mel-frequency cepstral coefficient extraction in Java for 4 000 labelled speech samples.
  • Stored computed features and labels in a normalised SQL schema, enabling ad-hoc analysis for research insights.
  • Produced Tableau heatmaps correlating feature clusters with speaker demographics to support conference findings.
Student Feedback Collector
Tools Used: Java

Certifications

C Programming — CodeChef
Salesforce AI Associate — Salesforce
Wipro Java Certificate — Wipro

Achievements

  • Cleared two levels in MSME Idea Hackathon

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