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Data Science with less than a year in Machine Learning, Deep Learning, and Data Analysis.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Science student with hands-on experience in Machine Learning, Deep Learning, and Data Analysis. Skilled in Python and building predictive models to solve real-world problems. Seeking an opportunity to apply analytical skills and contribute to data-driven decision-making.
Vidyalankar School of Information Technology
Bachelor of Science · Data Science
August 1, 2023 – June 30, 2026
SIES College of Arts, Science and Commerce
HSC (Science) Maharashtra State Board · Science
June 1, 2020 – May 31, 2021
SIES High School
SSC Maharashtra State Board
June 1, 2018 – May 31, 2019
Customer Segmentation & Churn Prediction
June 1, 2026 – Present
Performed RFM analysis and applied clustering for customer segmentation. Built churn prediction model using supervised ML algorithms. Achieved 94% accuracy and visualized insights using Power BI dashboard.
Suicide Risk Detection (ML & NLP)
June 1, 2026 – Present
Applied NLP techniques for text preprocessing and feature extraction. Built classification model to predict suicide risk using LSTM. Achieved 96% accuracy after model tuning.
Loan Approval Prediction
June 1, 2026 – Present
Conducted Exploratory Data Analysis (EDA) and feature engineering. Built classification models using Logistic Regression and Random Forest. Optimized model performance through hyperparameter tuning. Achieved 97% accuracy on test dataset.
Python
IIT Bombay
June 1, 2026 – Present
SQL Intermediate
Sololearn
June 1, 2026 – Present
DataNetWork
IIIT Kottayam
June 1, 2026 – Present
Introduction to R
Great Learning
June 1, 2026 – Present
Data analytics Job Simulation
Deloitte
June 1, 2026 – Present
Technology Job simulation
Deloitte
June 1, 2026 – Present
Getting Started with AWS IoT
AWS Training & Certification
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a focus on common data science problems (prediction, segmentation) and a willingness to learn new tools and techniques, as evidenced by various certifications. The projects are diverse enough to indicate a broad interest within the data science domain. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
The candidate lists problem-solving, communication, teamwork, and analytical thinking as soft skills. These are crucial for a Data Science role. However, without practical work experience, the operational fit and application of these skills in a professional setting are unproven. The academic projects suggest an ability to work independently on defined problems.