ML Engineer with less than a year in Data Analysis & Machine 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
Aspiring Data Scientist with strong foundation in Python, SQL, Machine Learning, and Data Analysis. Skilled in EDA, Feature Engineering, Predictive Modeling, and Statistical Analysis. Hands-on experience building ML models using Scikit-learn and processing datasets with PySpark. Familiar with NLP concepts, cloud platforms, and data pipelines.
Indore Institute of Science and Technology
B.Tech · Computer Science and Engineering
August 1, 2020 – June 30, 2024
Y.B.K Inter College, Muzaffarpur
Intermediate
June 1, 2018 – May 31, 2020
R.K High School Shahi, Muzaffarpur
Matriculation
June 1, 2016 – May 31, 2017
Revature
Data Engineer Trainee
September 1, 2025 – June 1, 2026
India
Spam Email Classifier using NLP
June 1, 2026 – Present
Built an NLP-based spam detection system to classify emails and SMS messages as spam or ham. Performed text preprocessing including tokenization, stopword removal, and text cleaning. Applied TF-IDF and CountVectorizer techniques for feature extraction. Trained Logistic Regression and Naive Bayes models for spam classification. Evaluated performance using accuracy, precision, recall, and confusion matrix metrics.
Real-Time Traffic Data Analysis Pipeline
June 1, 2026 – Present
Processed real-time traffic datasets using PySpark for large-scale analysis. Identified congestion patterns and peak traffic hours through statistical analysis. Performed data cleaning, aggregation, and transformation for reporting pipelines. Generated analytical insights for traffic monitoring and decision-making.
View ProjectSQL and Relational Databases 101
IBM Cognitive Class
June 1, 2026 – Present
Databricks Certified Associate Developer for Apache Spark
Databricks
January 1, 2026 – January 1, 2026
Cultural Fit Analysis
The candidate's profile shows a strong inclination towards data science and machine learning, aligning well with a technical, data-driven culture. The diversity of projects (NLP, real-time data analysis) and continuous learning through certifications suggest a curious and adaptable individual. The experience as a Data Engineer Trainee and personal projects indicate a practical, hands-on approach. The target role of ML Engineer is a good fit for the skills and interests demonstrated.
Soft Skills & Operational Fit
The candidate demonstrates a proactive attitude towards learning and skill development through certifications and personal projects. The experience in building data pipelines and performing EDA suggests an organized and analytical approach to problem-solving. The project descriptions indicate an ability to work independently on technical challenges. However, without direct interview data, specific soft skills like teamwork, communication under pressure, or leadership cannot be fully assessed.