Frontend Developer with less than a year in Frontend Development & Data Science
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Assessing your cultural and operational fit
Motivated CS Engineering fresher seeking roles as Data Engineer, Data Analyst, Frontend Developer, or Quant/Algo Trading Developer. Proficient in Python, SQL, JavaScript, and Machine Learning, with hands-on experience in data pipelines, predictive modeling, and algorithmic trading backtesting.
Prof. Ram Meghe Institute of Technology and Research
Bachelor of Engineering · Computer Science
August 1, 2022 – June 30, 2026
Octanet Tech Services
Frontend Web Development Intern
September 1, 2025 – Present
India
Algorithmic Trading Backtesting Framework
January 1, 2026 – June 1, 2026
Developed and backtested multiple algo trading strategies (RSI mean-reversion, MACD crossover, Bollinger Band breakout) on historical data. Integrated Alpaca Trading API for paper trading; computed Sharpe Ratio, max drawdown, and win rate for strategy evaluation. Automated data ingestion pipeline using yfinance and Alpha Vantage for multi-ticker OHLCV data processing.
Stock Price Prediction using LSTM
January 1, 2026 – June 1, 2026
Built a deep learning model using LSTM networks to predict stock closing prices from historical OHLCV data via yfinance API. Applied time-series preprocessing (normalization, sliding window sequences) and trained the model achieving low RMSE. Visualized predicted vs. actual price trends with Matplotlib to evaluate model performance across multiple ticker symbols.
Doctor Online Appointment System
January 1, 2026 – June 1, 2026
Built a full-stack appointment booking app with responsive HTML5/CSS3/JS frontend and RESTful Node.js backend. Implemented user authentication, appointment scheduling APIs, and MySQL database with optimized indexing. Ensured cross-device compatibility and intuitive UI/UX, reducing booking friction for patients and providers.
ML Approach for Deforestation Prediction
January 1, 2026 – June 1, 2026
Applied Random Forest, Decision Tree & SVM algorithms to forecast deforestation patterns using real-world environmental datasets. Performed end-to-end preprocessing, feature selection & hyperparameter tuning; designed ETL pipelines improving data quality. Built interactive visualizations (Matplotlib, Seaborn) to communicate insights and support data-driven decision-making.
Real-Time Data Pipeline with Apache Kafka & Spark
January 1, 2026 – June 1, 2026
Designed a real-time streaming pipeline ingesting live data via Kafka producers, processed with PySpark Structured Streaming. Orchestrated batch ETL workflows using Apache Airflow DAGs and stored transformed data in AWS S3 for downstream analytics. Implemented data quality checks and schema validation at each pipeline stage, reducing downstream errors significantly.
AWS Certified (AI/ML)
Amazon Web Services
June 1, 2026 – Present
Python for Data Science & ML Bootcamp - Pandas, NumPy, Scikit-learn, data visualization
Udemy
June 1, 2026 – Present
AI for Beginners - AI fundamentals, supervised/unsupervised learning, real-world AI applications
HP Life
June 1, 2026 – Present
SQL 5-Star Gold Badge - Advanced joins, CTEs, window functions, query optimization
HackerRank
June 1, 2026 – Present
Responsive Web Design & JavaScript Algorithms – HTML5, CSS3, ES6+, React.js basics
freeCodeCamp
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects are diverse, spanning algorithmic trading, machine learning, and full-stack development, indicating a broad interest in technology. While the target role is Frontend Developer, the candidate's background in data science and AI suggests a versatile mindset. The certifications in AWS, Python for Data Science, and Responsive Web Design show a commitment to continuous learning and skill development, which aligns well with a growth-oriented culture. However, the primary focus on data science in academic projects might indicate a broader interest beyond just frontend, which could be a factor in long-term role alignment.
Soft Skills & Operational Fit
The candidate demonstrates collaboration skills through participation in daily standups and sprint planning. Their project descriptions indicate an ability to work on complex problems and present findings, suggesting good problem-solving and communication skills. The academic projects show initiative and a structured approach to development.