Data Scientist II (Remote, ROU)

Candidates should have at least 2 years of applied machine learning research expertise in developing and deploying production systems. They must be skilled at extracting actionable insights from large, high-dimensional, sparse data across the machine learning pipeline and driving real-world impact. Proficiency with Python, Deep Learning frameworks (Tensorflow, Pytorch), cloud technologies in a Linux environment, and expertise in training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers are required. Familiarity with GPU-based technologies such as CUDA, CuDNN, and TensorRT is also necessary. A strong desire to work in the field of cybersecurity, excellent communication skills for simplifying complex concepts, and robust problem-solving and critical-thinking skills are essential. A PhD in Computer Science, Statistics, Mathematics, or a related field with a focus on data science, machine learning, or AI, along with a track record of research contributions in high-impact, peer-reviewed scientific journals, are considered bonus points.