BN31P2-Data Scientist

Job Summary

This is an individual contributor role on the Data Analytics and Insights (DAI) team, which builds the AI that powers CAS’s scientific information products. As a data scientist, you will build the models, agents, and AI-powered features that ship in those products, working alongside data engineers, product managers, and scientific domain experts. This role requires dual-domain expertise: you must be both a capable software engineer and formally trained in a scientific discipline relevant to CAS’s customers (chemistry, life sciences, materials science, or a related field).

Job Accountability

• Develop and deploy agent-based workflows, retrieval-augmented generation (RAG) pipelines, and LLM-powered features within CAS products using Python, LangGraph/LangChain, and related tools.
• Develop and deploy machine learning models that ship inside CAS products (for example property, toxicity, or biologic developability prediction), using your scientific training to inform feature design and to validate model behavior.
• Ground agentic and predictive features in CAS’s authoritative scientific content, and use your scientific training to judge whether system outputs are accurate, defensible, and useful to researchers.
• Engineer for production, not for demos: deliver clean, tested, well-documented software with appropriate safeguards such as content safety guardrails, entitlement-based access control, evaluation, and model fallback, following team engineering standards (unit, integration, and end-to-end tests, containerized development, and CI/CD practices).
• Work with product managers, scientific domain experts, data engineers, and other teams to translate scientific and research requirements into working technical solutions.
• Contribute to evaluation frameworks for GenAI systems, focusing on accuracy, reliability, scientific correctness, and continuous improvement of agentic features.
• Build and operate solutions on cloud infrastructure (AWS, Azure, GCP, or similar), supporting the production deployment and ongoing operations of AI systems.
• Use agentic software development tools such as Claude Code as a core part of the daily workflow to accelerate delivery and maintain quality.
• Contribute to DAI’s innovation and competitive-intelligence work by prototyping emerging AI capabilities and running structured experiments that test where AI can replicate or extend CAS capabilities.
• Stay current with advances in generative AI and agentic architectures, and share knowledge with the team through demos, documentation, and internal learning sessions.

Required Qualifications

• Bachelor’s degree or higher in a scientific discipline relevant to CAS’s customer domains (chemistry, life sciences, materials science, or a closely related field).
• The ability to read scientific content in your field and reason about it accurately enough to evaluate the outputs of AI systems that serve working scientists (for example, recognizing when a predicted property or a generated answer is wrong).
• 2+ years of professional experience in software engineering, applied machine learning, or data science, with demonstrated delivery of working systems.
• Strong Python programming skills with solid software engineering fundamentals (version control, testing, code review, documentation).
• Hands-on experience building applications with large language models, including agentic workflows, RAG, prompt engineering, or similar patterns.
• Experience with or strong interest in agentic AI frameworks such as LangGraph, LangChain, or equivalent platforms.
• Proficiency with agentic software development tools (e.g., Claude Code or similar AI-assisted development environments).
• Experience deploying and operating software in at least one cloud environment (AWS, Azure, or GCP).

Desired But Not Required

• Graduate degree (M.S. or Ph.D.) in a scientific discipline relevant to CAS’s customer domains, giving deeper command of the science behind the products.
• Coursework, a second degree, or equivalent experience in Computer Science, Engineering, or Statistics that complements the scientific training.
• Experience building and deploying predictive ML models in a scientific or regulated domain.
• Experience with cloud AI/ML services and model hosting platforms.
• Familiarity with containerized development workflows and API design.
• Experience with evaluation frameworks for AI/ML systems, including accuracy, reliability, and cost optimization.

Benefits

CAS offers a competitive salary and comprehensive benefits package, including a generous vacation plan, medical, dental, vision insurance plans, and employee savings and retirement plans. Candidates for this position must be authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. EEO/Disabled/Veteran