Senior Data Scientist 1 (AI)

Location: Hybrid, requiring 2–3 days onsite in Novato, California; the role supports Technical Operations across Novato and San Rafael.

Company

hirify.global is a biotechnology company developing medicines for patients with significant unmet medical needs through genetics and molecular biology research.

What you will do

• Identify and frame AI opportunities across technical development, manufacturing, quality, and supply chain.
• Own portfolio planning, solution design, development, deployment, and end-to-end project delivery.
• Acquire, prepare, and govern data from MES, LIMS, QMS, ELN, SAP, and PI systems.
• Build machine learning and AI models for process monitoring, anomaly and root-cause analysis, yield and cycle-time optimization, and intelligent document processing.
• Develop GenAI solutions such as RAG systems, semantic search, Q&A assistants, and workflow copilots.
• Operationalize models through reproducible MLOps pipelines, dashboards, documentation, training, and value-realization tracking.

Requirements

• Master’s degree or MBA in Data Science, Computer Science, Statistics, or a related field.
• 7+ years of hands-on experience delivering data and AI solutions in an industry setting.
• Advanced Python and SQL; experience with databases, Azure Databricks, data modeling, and data engineering pipelines.
• Experience with GenAI pipelines on Databricks, including chunking, RAG, vector indexes, Delta, Unity Catalog, MLflow, Spark, and workflows.
• Experience with Azure, business intelligence tools such as Power BI, Tableau, or Spotfire, and Python web frameworks such as Dash, Flask, or Streamlit.
• Biotech or biopharma operations experience, collaboration with technical and operational SMEs, and familiarity with Computer System Validation documentation in regulated environments.

Culture & Benefits

• Work in a data-driven Technical Operations organization connecting research and development with commercial operations.
• Support rigorous regulatory, quality, and safety standards in a regulated biotechnology environment.
• Collaborate with engineering, manufacturing, quality, supply chain, IT, business SMEs, and data specialists.
• Contribute to continuous improvement, AI standards, data literacy, and a community of practice.