On-site
Full Time
About the Company We are seeking a strategic and research-driven Senior Data Scientist to join our global data team. This role is designed for an intellectually curious and impact-oriented individual contributor who can transform deep research into production-grade, real-world solutions—ranging from predictive modeling for hurricane forecasting to optimization in the medical device space. You will also have opportunities to contribute to advanced AI research, including LLMs and generative models. About the Role This role is designed for an intellectually curious and impact-oriented individual contributor who can transform deep research into production-grade, real-world solutions. Responsibilities 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. Qualifications Education: Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Physics, or related analytical disciplines. Experience: 5–10 years of industry experience in data science or applied machine learning (exceptional candidates with PhDs or track record of publications). Prior experience in startup environments or big tech is highly desirable. Proven track record in developing production-level solutions and delivering measurable impact from research. Required Skills 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. Preferred Skills Strong mathematical and analytical foundations. Deep intellectual curiosity and hunger for innovation. Self-driven and capable of owning the full research-to-deployment cycle. Strategic thinker who connects data science to business value and delivery performance. Flexibility to adapt to domain-specific tools and platforms (e.g., cloud infra, annotation pipelines). Show more Show less
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