Senior Data Scientist II

Overview

In this role you will design and deliver advanced AI, NLP, and generative AI solutions to power knowledge discovery and decision support for scientific data. You will build production-ready ML systems and collaborate across teams to turn complex challenges into scalable, impact-driven solutions. You’ll work with LLM-based workflows, RAG, and validation frameworks to ensure trusted performance. This role sits at the intersection of science, data, and engineering, delivering tangible user impact.

Pay / Benefits

• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals

Responsibilities

• Design, build, and evaluate 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, QA, and evidence-grounded insights
• Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern AI techniques
• Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows
• Establish robust evaluation, experimentation, and monitoring frameworks for quality, trust, performance, and reliability
• Write production-ready Python code and collaborate with engineering teams to deploy solutions at scale
• Provide technical leadership and mentoring to support high-quality delivery and continuous improvement

Key requirements

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

• Strong communication
• Collaboration
• Mentoring
• Python
• AI/ML frameworks
• NLP

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