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