
Saisathvik Bharatula
@saisathvikbharatula
I build data-driven machine learning pipelines, dashboards, and predictive applications using Python and SQL.
What I'm looking for
I've built end-to-end predictive systems including a customer churn pipeline that achieved 0.77 ROC-AUC and surfaced contract type and tenure as key retention drivers.
During AI and ML internships with EduNet Foundation and Cod Veda, I cleaned and analyzed thousands of records, trained regression and classification models, and improved predictive accuracy by approximately 15% through hyperparameter tuning. I also presented model-performance findings to stakeholders.
My projects include a Streamlit brain tumour detection app with 95% accuracy and Grad-CAM heatmaps, plus an interactive movie recommendation system using TF-IDF and cosine similarity.
Experience
Work history, roles, and key accomplishments
AI & ML Intern
EduNet Foundation
Jun 2025 - Jul 2025 (1 month)
Completed a structured 6-week ML internship covering supervised learning, model evaluation, and real-world AI applications. Built an end-to-end Employee Salary Prediction pipeline on 3,000+ records, from preprocessing and EDA to regression model training using Scikit-learn.
Education
Degrees, certifications, and relevant coursework
Raghu Engineering College
Bachelor of Technology, Computer Science and Engineering (AI & ML)
2022 -
Grade: 8.63 CGPA
Pursuing a Bachelor of Technology (Honors) in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning, achieving a CGPA of 8.63.
Sri Chaitanya Junior College
Intermediate, MPC (Mathematics, Physics, Chemistry)
2020 - 2022
Grade: 61.4%
Completed Intermediate education in the MPC stream with a percentage of 61.4%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Portfolio
github.com/saiSathvikbharatulaJob categories
Skills
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