Tejas Navalkhe

Freelance AI/ML Engineer

Self Employed•  September 2024 - Present•  Remote

• Developed and deployed end-to-end AI/ML solutions across fintech, edtech, and algorithmic trading domains, including real-time trading systems using Python, Flask, Redis, and WebSocket. • Built NLP and content-based course recommendation engine using TF-IDF, Word2Vec, BERT, and GPT models; implemented automated retraining pipelines and integrated both with cloud-based platforms. • Designed scalable REST APIs with Flask/FastAPI to serve real-time predictions; integrated with AWS services (EC2, S3, RDS) and Dockerised ML models for deployment and testing. • Automated data pipelines and web scraping using Python; executed hyperparameter tuning and A/B testing to optimize model performance.

Data Science Intern

Co Wheels Car Club•  May 2024 - September 2024•  Newcastle, United Kingdom

• Designed and developed a dynamic pricing model to optimize car-sharing profitability, leveraging machine learning models for 5 vehicle types. • Analysed historical booking data (2019-2024) from 30,000+ users across 600+ vehicles (including 200+ electric vehicles) to predict optimal hourly and daily pricing based on location popularity, peak hours, time of day, and seasonality. • Developed a web-based simulation tool using Flask and JavaScript, enabling real-time adjustments of pricing strategies and visualisation of their impact on revenue. • Increased projected revenue by 19.32% compared to static pricing models by implementing demand-based pricing strategies. • Automated data preprocessing and feature engineering for 39 variables, improving prediction accuracy and reducing manual data processing time by 40%. • Reduced integration errors by 25% by automating data synchronisation between the pricing tool and Co Wheels’ booking system. • Provided business insights that helped Co Wheels evaluate a transition from fixed pricing to a dynamic pricing model, enhancing profitability while maintaining user satisfaction.

Freelance Software Engineer - Algorithmic Trading

Finvestox Capital•  September 2022 - April 2024•  Remote, India

• Designed and implemented an algorithmic trading system with sub-millisecond trade execution, increasing trading volume by 20% and returns by 10% in three months. • Developed a real-time pricing data pipeline using Redis caching, improving data retrieval speed by 35% and ensuring 99.9% uptime for trading insights. • Built and deployed an automated trading platform with risk management for futures and options, integrating automated broker logins via Selenium and TradingView-based forecasting, reducing trade execution time by 30%. • Developed an interactive financial dashboard with Plotly, enhancing real-time analytics accuracy by 25% for better trading decisions. • Deployed on AWS using Docker, improving scalability and execution speed by 50%, and utilised SQL with forecasting models for continuous data availability. • Implemented a Redis pub/sub model for multi-server communication, ensuring efficient data flow between stock analysis and trade execution servers.

Web Development Intern

Vitaecura Consultancy Services•  July 2022 - September 2022•  Indore, India

• Worked on web development, UI/UX design, and IT operations. • Frontend Technologies: HTML, CSS, Bootstrap, jQuery, JavaScript. • Assisted in business development and IT project management.

Newcastle University

Computer Science, Master of Science in Data Science (With Specialisation in Artificial Intelligence)•  September 2023 - August 2024•  Percentage: 73.3

Relevant Coursework: Data Visualisation, Exploratory Data Analysis (EDA), Statistics for Data Science, Big Data Technology, Machine Learning, Deep Learning, Image Informatics, Data Management. Projects: 1. Fine-Grained Aircraft Model Classification (DenseNet201, Optimisation, Image Augmentation) 2. Performance Optimisation of Large-Scale Data Processing (Databricks, Big Data) 3. Time Series Student Engagement Prediction (Predictive Modelling – LSTM, Adam optimizer, ReLU activation function)

Prestige Institute of Engineering Management & Research

Computer Science & Engineering, Bachelor of Technology in Computer Science Engineering•  August 2019 - July 2023•  CGPA: 8.78

Relevant Coursework: Data Structure & Algorithm, Software Engineering, Project Management, Machine Learning, Database Management Systems, Computer Networks, Cloud Computing. Projects: 1. Transfer Village: A Large File Sharing Web Application (Amazon S3, EC2, Data Security) 2. Urjotsav: An Event Hosting Website with Payment Integration (Linux, Flask, Automation, Project Management) 3. The Virtual Assistance: Speech Recognition (Google Speech Recognition, SQL)