Job Title

Xenon Pharmaceuticals (NASDAQ:XENE) is a neuroscience-focused biopharmaceutical company dedicated to drug discovery, clinical development, and commercialization of life-changing therapeutics for patients in need. We are looking for great people who thrive in a respectful, collaborative, inclusive, and productive culture to join the Xenon team. About The Role We are seeking a Data Scientist to join the Computational Science & AI team to design, build, and deploy AI-powered applications that enable scientists to query, analyze, and visualize preclinical research data through natural language interfaces. This role sits at the intersection of data engineering, LLM orchestration, and scientific tooling. The successful candidate will build agentic AI systems over Oracle-backed scientific data, develop automated data analysis and signal processing pipelines, and deliver production-grade web applications across on-premises and cloud (Azure) infrastructure. The position will liaise with Research Scientists and IT Infrastructure managers to develop full-stack, user-friendly applications primarily in Python, deployed to Linux-based environments (on-premises servers or Azure cloud). The role places significant emphasis on integrating large language models both cloud-hosted (Azure OpenAI) and locally deployed (Ollama or similar) into scientific data workflows. The Data Scientist will collaborate with Research Scientists in In Vivo and In Vitro Pharmacology and IT Network Infrastructure Managers. This position reports to the Associate Director, Data Science in the Computational Science & AI group and will be based out of Vancouver, BC, Canada. This role is a 12-month contract position and is a full-time hybrid role with a minimum of 3 days in the office. Responsibilities Design and implement agentic AI systems that allow scientists to query Oracle databases and scientific data platforms using natural language, generating interactive plots and structured reports from preclinical data. Integrate large language models into scientific data workflows using both cloud-hosted services (Azure OpenAI) and locally deployed open-weight models (Ollama, vLLM, or similar), including prompt engineering, tool/function calling, guardrails, output validation, and structured output parsing. Design and implement retrieval-augmented generation (RAG) pipelines over scientific documents and database schemas to ground LLM responses in domain-specific context. Evaluate, benchmark, and select appropriate LLM backends (cloud vs. local, model size, quantization) based on latency, accuracy, cost, and data privacy requirements. Build scalable data models and ETL pipelines that surface scientific data through web-based applications and GUIs in Python (Plotly Dash, FastAPI). Use Docker to build, test, and deploy containerized applications across on-premises and Azure environments. Communicate effectively with scientific and technical stakeholders, including presenting methods, architectures, and results to broader audiences. Write detailed application and system documentation using GitHub Pages, Sphinx, or similar professional tooling. Act in accordance with Company policies, including, for example, the Code of Business Conduct and Ethics and ensure policies are understood and followed by direct reports, if any. Qualifications Bachelor''s degree (minimum) in Computer Science, Engineering, Mathematics, or a related quantitative field, with relevant experience in data engineering, LLM application development, and software development. Advanced Python programming skills: clean, well-documented, production-quality code with appropriate testing and error handling. Experience with SQL scripting and relational database systems (Oracle preferred), including query optimization and schema design. Demonstrated ability to work with LLMs and AI agent frameworks prompt engineering, retrieval-augmented generation (RAG), function/tool calling, structured output parsing, or similar orchestration patterns. Hands-on experience deploying and serving LLMs locally using Ollama, vLLM, llama.cpp, or similar inference frameworks, including model selection, quantization trade-offs, and GPU resource management. Proficiency with Python web frameworks for building interactive front-end applications (Plotly Dash and/or FastAPI), including working knowledge of HTML/CSS for UI refinement. Experience with Docker for building and deploying containerized applications. Strong Git workflows (branching, merging, pull requests) and familiarity with CI/CD tooling (GitHub Actions or similar). Comfortable working in Linux environments (Ubuntu), writing bash scripts, and managing applications on servers or VMs. Excellent written and verbal communication skills with a demonstrated ability to document systems and workflows professionally. Our Total Rewards program includes base salary, target bonus, and stock options, as well as a full range of benefits including medical, dental, vision, short- and long-term disability, accidental death & dismemberment, and life insurance programs, Employee Assistance Program, travel insurance, and retirement savings programs with company matching contributions. Xenon encourages time to rest and re-charge through vacation, personal days, sick days, and an end-of-year company shutdown. Xenon highly values employee development and has an expanding Training, Learning & Development program, including a Tuition Assistance program for advanced degrees. Compensation Range: CA$117.2K - CA$148.2K #J-18808-Ljbffr