Machine Learning Engineer with 4+ years in Data Analytics & Deep Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented seeking to transition into the Machine learning and python Developer. Equipped with a strong foundation in Python, SQL, and Machine learning through training and personal projects.
St. Mary's Group of Institutions, Hyd.
Bachelor of Technology
August 1, 2018 – June 30, 2022
NRI junior College, Hyd.
Intermediate
June 1, 2016 – May 31, 2018
Wine Classification Using Machine Learning.
June 25, 2026 – Present
Random Forest with feature Importance and Tree Visualisation. Training the Dataset and Testing the Dataset by Splitting. Model checking, predicting the values, that are accuracy in metrics by this Random Forest Classifier the accuracy is 97.8%. Visualizing one tree from Random Forest. Boosting on wine dataset, with the Adaboost Classifier, the accuracy is 97.2%. Gradient Boosting Classifier, the accuracy is 94.4%. Feature Importance that, which is more important from the Dataset. In Stochastic Gradient Boosting Trees, the test accuracy is nearly 100%.
Jamboree Admission Predictor at IVY League Colleges Using EDA.
June 25, 2026 – Present
A predictive model to estimate students admission chances at prestigious Ivy League colleges . The model analyzes critical admission factors including standardized test scores (TOEFL, GRE) academic performance (CGPA), and application components (SOP, LOR) to identify patterns in historical admission data. This data-driven tool helps prospective graduate students assess their competitive standing and make informed decisions about their applications to highly selective institutions.
Web Developer
Unknown
June 1, 2026 – Present
Fullstack Python Developer
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects align with the target role of Machine Learning Engineer, demonstrating interest and foundational skills. The projects show a focus on predictive modeling and classification, which are core to ML roles. However, the lack of diverse project types (all academic) and professional experience limits the assessment of broader cultural fit and adaptability.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to articulate technical processes and outcomes. However, without direct work experience or psychometric test results, it is difficult to assess stress handling, team collaboration, or other operational fit aspects.