Senior Data Scientist

Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Physics, or related analytical disciplines. 5–10 years of industry experience in data science or applied machine learning (exceptional candidates with PhDs or track record of publications) Advanced programming in Python (non-negotiable). Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow). Strong grasp of machine learning concepts and familiarity with LLMs. Experience with GCP, LLM fine-tuning, and feedback-driven data annotation processes preferred. Ability to design and interpret benchmarks and evaluation metrics with a strategic mindset.

Conduct applied research and develop data science solutions for high-impact, real-world problems. Design and implement data-centric evaluations to improve model outcomes and benchmark relevance. Collaborate with cross-functional teams (data ops, research, engineering) to align priorities on data quality, modeling, and infrastructure. Contribute to building or enhancing task taxonomies and scalable QA systems to improve training data signals. Translate research outcomes into business value by driving measurable performance improvements. Stay abreast of generative AI trends and their implications for data utility, model benchmarking, and downstream performance.