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Data Science with less than a year in ML pipelines & Generative AI.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Fresh B.Tech graduate and Data Science professional with hands-on internship experience building end-to-end predictive ML pipelines and deploying models via Flask. Skilled in Python, Scikit-Learn, SQL, and Generative AI (LLMS, RAG). Certified by Stanford, AWS, and IBM. Passionate about translating raw datasets into actionable predictions that drive retention and smarter institutional decisions.
PACE Institution of Technology and Sciences
B.Tech · Electronics & Communication Engineering
August 1, 2021 – June 30, 2025
Saiket Systems
Data Science Intern
January 1, 2026 – March 1, 2026
Hyderābād, Telangana, India
Predictive Student Academic Performance System
January 1, 2025 – December 31, 2025
Engineered an end-to-end ML system forecasting student score variances from attendance, assignment statistics, and study durations. Trained and validated Linear Regression and Random Forest Regressors; evaluated performance using MAE and R2 to minimize prediction error. Deployed a scalable Flask web backend delivering real-time inference via dynamic user-input forms, creating a complete data-to-decision pipeline.
Telecom Customer Churn Prediction
January 1, 2025 – December 31, 2025
Designed a binary classification system to predict subscriber churn from historical usage and billing metrics, enabling proactive retention strategies. Tuned Decision Tree and Logistic Regression models via hyperparameter optimization, maximizing precision and recall on imbalanced class distributions. Built clean feature transformation layers managing class imbalance without synthetic oversampling, preserving real-world data integrity.
Statistical Learning - Verified Professional Certificate via edX
Stanford Online
June 1, 2026 – Present
Introduction to Machine Learning on AWS – AWS Training & Certification via edX
Amazon Web Services
June 1, 2026 – Present
Data Science Programme - Certificate of Excellence
ExcelR
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internship demonstrate a strong interest and foundational skill set in data science. The projects cover both regression and classification tasks, showing diversity in problem-solving approaches. The certifications further highlight a commitment to continuous learning and staying updated with industry trends (e.g., AWS ML). The candidate's profile aligns well with a data-driven culture that values practical application and continuous improvement. However, the experience is limited to an internship and academic projects, which might require more mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience suggest an ability to work on practical problems, translate data into actionable insights, and deploy solutions. The focus on 'real-time model inference' and 'production-grade web applications' indicates an understanding of operationalizing ML models. However, without specific psychometric or English test scores, a detailed assessment of soft skills like logical reasoning, work attitude, stress handling, and team collaboration is not possible.