Help & Supportcareers@gravityer.com
Python Engineer with less than a year in Python, databases, and 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 Python Developer with a strong foundation in Python, databases, and software development fundamentals. Experienced in academic projects and collaborative coding environments.Seeking a opportunity to apply skills, gain industry exposure, and grow as a developer.
M.S.Ramaiah Institute of Technology
Bachelor of Engineering · Information Science and Engineering
August 1, 2023 – Present
P.V.P. Polytechnic
Diploma · Computer Science and Engineering
August 1, 2020 – June 30, 2023
Expense Tracker with ML-Based Prediction
June 28, 2026 – Present
Developed a full-stack expense tracking web application using Django framework following MVC architecture. Designed REST-like functionality handling HTTP methods (GET, POST) for expense CRUD operations. Implemented data visualization using Chart.js to display monthly trends and category-wise spending. Built a Random Forest ML model to predict next months expenses using historical and real-time data. Ensured user-specific data security by filtering data per authenticated user. Integrated CSV-based historical data with live database inputs for improved prediction accuracy
AI-Powered NoSQL / MongoDB to SQL Converter
June 28, 2026 – Present
Built a Generative AI-powered web application to convert NoSQL and MongoDB JSON data into structured SQL queries. Implemented schema inference to automatically generate CREATE TABLE and INSERT statements. Integrated LLaMA 3.1 via Groq API using prompt engineering for intelligent SQL generation. Developed an interactive Streamlit UI with JSON input, file upload, and downloadable SQL output. Supported multiple SQL dialects including MySQL, PostgreSQL, and SQLite
EARLY DETECTION OF BANKRUPTCY USING MACHINE LEARNING
June 28, 2026 – Present
Developed a predictive model to identify potential bankruptcies using financial ratios and historical company data. Collected and prepared historical company financial statements and computed key financial ratios (liquidity, leverage, profitability, efficiency) to capture the financial stability and operational performance of firms. Engineered features by transforming raw financial variables into predictive signals, handling missing values, outliers, and skewed distributions to improve model reliability. Selected LightGBM as the core classification model due to its gradient boosting strategy, ability to handle non-linear relationships, and superior performance on structured financial datasets. Evaluated model performance using accuracy, precision, ROC, and AUC to assess prediction reliability.
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse set of interests, ranging from web development to machine learning and generative AI, which aligns with a dynamic and innovative work environment. The focus on practical applications (expense tracker, bankruptcy prediction, NoSQL to SQL converter) suggests a problem-solving mindset. The target role of 'Python Engineer' is well-aligned with the candidate's primary programming language and framework experience. However, the lack of professional experience means cultural fit in a corporate setting (e.g., collaboration, conflict resolution, adaptability) is largely unproven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, manage project scope (full-stack development, ML model integration), and apply structured approaches (MVC architecture, feature engineering). The academic nature of projects suggests a learning-oriented individual. However, without professional experience, the operational fit regarding team collaboration, agile methodologies, and handling production-level challenges is unassessed.