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Sree Kirthana

@sreekirthana

Machine Learning practitioner at Cognifyz Technologies who achieved 98% accuracy and built a syllabus-planning AI agent.

India

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What I'm looking for

I'm seeking a full-time role in Machine Learning, Data Science, or Software Engineering where I can ship measurable impact through data-driven solutions.

At Cognifyz Technologies, I developed and deployed Python and TensorFlow models for restaurant-rating prediction and cuisine classification, achieving 98% accuracy on the production validation set. I also created evaluation dashboards for precision, recall, and F1.

As a Data Engineering Intern at Cognifyz Technologies, I built Python and SQL pipelines transforming more than 10,000 records a day. I standardized ETL routines and documentation, helping raise pipeline reliability to 99.5% uptime.

At CodSoft, I analyzed more than 15,000 records to identify trends and anomalies, then presented six actionable insights. My work used Python, pandas, and NumPy for data manipulation, hypothesis testing, and visualization.

I built StudyPilot, an AI agent that processes syllabus PDFs and generates priority-weighted study schedules. Using Llama 3.1, it extracted topics, deadlines, and weightings with 96% accuracy across 15 sample syllabi.

Experience

Work history, roles, and key accomplishments

Data Science Intern

CodSoft

Jan 2026 - Jan 2026 (0 months)

Analyzed 15K+ records to surface trends and anomalies, delivering 6 actionable insights. Collaborated with team members to ensure 98% data integrity across all analysis deliverables.

Python Pandas NumPy Data Analysis Statistical Analysis Data Visualization Hypothesis Testing

Data Engineering Intern

Cognifyz Technologies

Nov 2025 - Dec 2025 (1 month)

Built Python and SQL data pipelines transforming 10K+ records per day, improving team throughput by 18%. Standardized ETL routines and documentation, lifting pipeline reliability to 99.5% uptime.

Python SQL Data Pipelines ETL Data Quality Documentation

Machine Learning Intern

Cognifyz Technologies

Sep 2025 - Nov 2025 (2 months)

Developed and deployed machine learning models in Python and TensorFlow for restaurant-rating prediction and cuisine classification, achieving 98% accuracy. Collaborated with a team of 5 engineers, reducing model error rate by 22% across four sprint releases.

Python TensorFlow scikit learn Machine Learning Model Deployment Dashboard Evaluation Precision Recall