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AI Engineer with less than a year in programming, data analysis, and machine learning.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science Engineering (AI & ML) undergraduate graduating in 2026 with strong foundations in programming, data structures, and problem solving. Experienced in developing data-driven applications using Python and SQL, performing large-scale data analysis, and building predictive models. Skilled in writing clean and efficient code, working with Git version control, and analyzing large datasets to derive insights. Passionate about building scalable software solutions and continuously learning new technologies.
CMR Technical Campus
B.Tech · Computer Science Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Vehicle Price Analysis & Prediction
June 1, 2025 – June 1, 2026
Analyzed a dataset of 50,000+ vehicle records using Python and SQL to identify pricing trends and feature impact. Developed machine learning regression models achieving 7% Mean Absolute Percentage Error (MAPE). Designed optimized SQL queries for data extraction and aggregation, improving reporting efficiency by 20%. Performed data preprocessing, feature engineering, and model evaluation to improve prediction accuracy. Created data visualizations using Matplotlib and Seaborn to communicate insights for decision making.
Task Tracker Analytics System
June 1, 2025 – June 1, 2026
Processed and analyzed productivity data for 1,000+ users to identify workflow bottlenecks. Developed Python scripts and SQL queries to summarize tasks by status, priority, and category. Automated reporting processes which reduced manual reporting time by 30%. Generated analytical dashboards and reports to support operational decision making.
Retail Sales Analysis & Forecasting
June 1, 2025 – June 1, 2026
Performed exploratory data analysis on 250,000+ retail transactions to identify sales trends and seasonality. Built ARIMA forecasting model achieving 6.5% MAPE to predict monthly sales. Developed SQL queries to summarize revenue and category performance improving reporting efficiency by 25%. Generated insights that contributed to a 12% reduction in inventory overstock.
Business and Data Analytics
Infosys Springboard
January 1, 2026 – Present
Generative AI Certification
Google Cloud
January 1, 2024 – Present
Google Cloud Data Analyst Certification
Google Cloud
January 1, 2024 – Present
AWS Academy Cloud Foundations
EduSkills
January 1, 2024 – Present
Python Programming Certification
Coursera
January 1, 2023 – Present
Cultural Fit Analysis
The candidate is an undergraduate with academic projects, which inherently limits the diversity of real-world scenarios and team collaboration experiences. While the projects are relevant to data analysis and machine learning, they are all academic in nature. The certifications show initiative and a commitment to learning, which is a positive cultural indicator. However, the lack of professional experience or diverse project types (e.g., open-source contributions, internships) suggests a developing understanding of broader industry practices and team dynamics.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to analyze large datasets, identify trends, and automate reporting, suggesting strong analytical thinking and problem-solving skills. The focus on improving efficiency (e.g., 20% reporting efficiency, 30% reduced manual reporting time) highlights a results-oriented approach. However, without direct work experience or psychometric test results, it's difficult to assess stress handling, teamwork, or direct communication in a professional setting.