We’re looking for a Data Scientist with a strong foundation in machine learning and a practical approach to building scalable, production-ready models. The ideal candidate is experienced in working with time-series data, deep learning architectures, and natural language processing
-Job Description -Collect, clean, and transform structured and unstructured data for modeling -Choose appropriate machine learning models based on problem requirements, and evaluate performance using relevant metrics -Optimize hyperparameters and refine model performance through iteration -Communicate insights and results clearly through visualizations, reports, and presentations -Deploy models into production environments and monitor performance to ensure long-term reliability and scalability
-Key Qualifications -Mid to senior-level in data science and applied machine learning -Solid understanding of core ML concepts and hands-on experience implementing well-established models -Experience with deep neural networks such as RNNs, LSTMs, and other architectures suited for time-series and numerical analysis -Strong background in NLP; experience with fine-tuning or modifying Large Language Models (LLMs) is a plus -Proven ability to develop and deploy scalable ML solutions in real-world applications -Proficiency in Python; familiarity with R is a bonus