Senior AI & Analytics Engineer Location: Seattle, WA – (Hybrid: 50% Onsite) 1-year contract to hire Job ID: 82821 Pay Range: $85-$95/hour About the Role We are seeking a highly skilled Senior AI & Analytics Engineer to drive the development of next-generation analytics infrastructure and AI-powered decision tools within a global, highly regulated healthcare environment. This role combines expertise in data engineering, analytics modeling, and AI/ML deployment to power intelligent insights across clinical trials, cell therapy operations, and commercial performance. You’ll lead end-to-end delivery—from data ingestion and transformation to visualization and model deployment—empowering teams with actionable intelligence through clean pipelines, robust architecture, and data storytelling. Key Responsibilities • Data Engineering & Architecture • Design, implement, and optimize cloud-based data pipelines using Python, SQL, Airflow, and ETL orchestration tools. • Build scalable data transformations with dbt and deploy to platforms such as Snowflake or BigQuery. • Analytics & Visualization • Develop curated datamarts, semantic models, and interactive dashboards using Tableau or Power BI. • Translate complex metrics and KPIs into visual insights and business impact stories. • Collaborate on metric definitions and data governance best practices. • AI & Machine Learning • Build, train, and operationalize machine learning models using Scikit-learn, TensorFlow, PyTorch, and MLFlow. • Explore unstructured data with NLP and Retrieval-Augmented Generation (RAG) techniques using LangChain, OpenAI APIs, and HuggingFace Transformers. • MLOps & Deployment • Develop production-grade ML pipelines with CI/CD workflows, containerization, and observability tools. • Integrate insights and models into decision support systems used by clinical and commercial operations. • Governance & Compliance • Ensure high-quality documentation of technical workflows and compliance with data integrity standards. • Maintain privacy and security best practices (e.g., HIPAA, GxP if applicable). Required Qualifications • 5+ years of experience in data engineering, analytics engineering, or applied machine learning • Strong programming skills in Python and SQL; experience with tools like Airflow, Prefect, or Domino • Hands-on experience with the modern data stack: dbt, cloud warehouses (Snowflake, BigQuery), version control, and CI/CD • Familiarity with MLOps, DataOps, and LLM toolchains including Langchain, OpenAI, and Hugging Face • Strong communication skills and the ability to work across multidisciplinary teams • Experience in regulated domains such as biotech, pharma, or life sciences Preferred Qualifications • Working knowledge of clinical trials, real-world evidence (RWE), or commercial analytics • Expertise in NLP, time-series forecasting, or image analytics in healthcare contexts • Master’s or PhD in a quantitative field such as Computer/Data Science, Public Health, Economics, or Statistics Top 5 Must-Have Skills (per Hiring Manager) 1. Proven experience in data engineering, analytics, or ML applications 1. Strong Python and SQL abilities 1. Hands-on experience with ETL orchestration tools (Airflow, Prefect, Domino) 1. Deep comfort with complex datasets and pipeline automation 1. Ability to communicate insights clearly and collaborate across functions