Data Scientist and Machine Learning Engineer with hands-on experience building and adapting production-oriented ML and AI solutions across time-series forecasting, recommendation systems, computer vision, NLP, speech processing, and LLM applications. Strong across the full delivery cycle: problem framing, data preparation, feature engineering, model training, evaluation, API integration, deployment, and iterative improvement. Able to translate business needs into practical ML systems and work effectively with product, engineering, and delivery teams.
CORE SKILLS
Machine Learning: supervised learning, classification, regression, clustering, anomaly detection, feature engineering, model evaluation, time-series forecasting
Deep Learning: TensorFlow, Keras, PyTorch, CNN, RNN, LSTM, GAN, transformers, transfer learning, fine-tuning
LLM / GenAI: OpenAI, Hugging Face, Transformers, Whisper, RAG, prompt engineering, LlamaIndex, agent workflows, LLM-based processing pipelines
Computer Vision / NLP / Speech: OpenCV, YOLO, OS2D, image processing, text classification, transcription, speaker diarization, OCR-related workflows
Backend / Product Delivery: Python, SQL, FastAPI, Flask, REST APIs, SQLAlchemy, Docker, Git, Jupyter, Jira, Confluence, Monday, AWS, Google Cloud
