Target roles: Machine Learning Engineer, Data Scientist, Data analyst, Software Engineer.
I am a skilled Python programmer and Machine Learning Engineer with a focus on building high-impact predictive systems. I specialize in applying advanced analytics to solve complex business problems, including Fraud Detection, Sales and Demand Forecasting, Credit Scoring, and Recommendation Engines.
With a strong foundation in mathematics and software engineering, I bridge the gap between data science and production-grade software. I have hands-on experience developing scalable backend services and APIs using FastAPI, as well as training custom models for NLP and Computer Vision.
My professional background includes fine-tuning and creating high-quality training datasets for Large Language Models (LLMs) like ChatGPT and Gemini, ensuring model accuracy and alignment. I am driven by innovation, technical challenge, and the delivery of scalable, data-driven solutions.
Re-implemented a carbon-box model incorporating the latest IPCC emission scenarios. Predicted global temperatures (2022–2100) based on varying CO2 levels using Python and SciPy.
Read PaperDeveloped a Hybrid Deep Learning model combining LSTM and GRU to predict atmospheric CO2. Achieved accuracy on par with traditional physics-based simulations.
Read PaperImplemented Active Learning, Self-training, and Co-training from scratch. Evaluated their performance on Sentiment Analysis tasks to determine the most computationally efficient method.
Read PaperBuilt a custom library for statistical analysis, including hypothesis testing, frequency distributions, and probability visualization tools. Optimized for performance.
Internal Tool