Senior Data Scientist

Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality., In this role, you will design and deliver advanced AI, NLP, and generative AI solutions that power knowledge discovery and decision support. You will work with complex scientific data and apply modern machine learning and LLM-based approaches to build scalable, reliable systems with real user impact. You will also collaborate across teams to turn complex challenges into practical, production-ready solutions., * Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications.

• Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation.
• Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques.
• Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows.
• Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability.
• Write production-ready Python code and partner with engineering teams to deploy solutions at scale.
• Provide technical leadership and mentoring to support high-quality delivery and continuous improvement., Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

• Practical experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field.
• Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems in applied or product-focused environments.
• Expertise working with LLMs, including fine-tuning, prompt engineering, grounding strategies, and responsible AI practices.
• Strong Python skills and solid machine learning fundamentals.
• Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks.
• Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact.
• Familiarity with cloud platforms and modern software engineering practices.
• Strong communication, collaboration, and mentoring skills.