Sr. Data Scientist 1

About Technical Operations
BioMarin’s Technical Operations group is responsible for creating our drugs for use in clinical trials and for scaling production of those drugs for the commercial market. These engineers, technicians, scientists and support staff build and maintain BioMarin’s cutting-edge manufacturing processes and sites, provide quality assurance and quality control to ensure we meet regulatory standards, and procure the needed goods and services to support manufacturing and coordinating the worldwide movement of our drugs to patients.

• Identify and frame AI opportunities across Technical Development, Manufacturing, Quality, and Supply Chain; translate ambiguous problems into tractable use cases with measurable outcomes.
• Maintain TOPS Data Science Portfolio of Projects. Participate in Portfolio prioritization, planning, solution design, development, and deployment.
• Lead Projects from start to finish by closely working with stakeholders, leadership and project team. Author business case, design, development and project implementation documents.
• Advance the Integrated Technical Data Strategy by defining roadmaps, value hypotheses, and success metrics that strengthen process robustness, speed, and cost/value realization.
• Acquire and prepare multi-source technical data (e.g., MES, LIMS, QMS, ELN, SAP, PI), ensuring quality, lineage, and context for AI development at scale.
• Engineer domain-aware features and reusable data assets that accelerate experimentation for manufacturing, quality, and supply analytics.
• Build and validate ML/AI models for use cases such as process monitoring, anomaly/root-cause analysis, yield and cycle-time optimization, and intelligent document processing.
• Develop GenAI solutions (e.g., RAG for SOPs/reports, Semantic search, Q&A assistants over technical data, workflow copilots) using approved enterprise platforms.
• Operationalize models (MLOps) with reproducible pipelines by closely working with Data Engineering team—data ingestion, training, evaluation, versioning, deployment—and monitor drift, performance, and data quality for continuous improvement.
• Collaborate with IT/Engineering to ensure scalable, secure, and supportable AI services aligned to TOPS environments and platform standards.
• Drive data visualization and decision support with clear narratives and dashboards that communicate model insights to engineers, operators, quality leads, and executives.
• Champion data integrity and documentation (e.g., model cards, validation records) consistent with TOPS quality expectations and regulated biotech practices.
• Educate and enable partners through demos, playbooks, and training that raise data/AI literacy and adoption across TOPS functions.
• Quantify and report value realization (e.g., cost avoidance, OEE improvements, cycle-time reduction, quality signal detection) and maintain a transparent backlog of AI initiatives.
• Promote “build-first” evaluations against internal platforms before third-party tools when requirements are met internally with better agility and cost efficiency.
• Contribute to TOPS AI standards (feature stores, evaluation frameworks, prompt/agent guidelines) and mentor peers to strengthen the data science community of practice.
• Stay current on AI advances (foundation models, time-series, causal inference, simulation/digital twins) and assess applicability to manufacturing, quality, and supply use cases.

• Advanced SQL and Python for data wrangling, feature engineering, modeling, and automation.
• Experience developing Python based web applications using frameworks such as Dash, Flask, Streamlit. Familiarity with HTML/CSS and TS frameworks (React) is a plus.
• Strong experience working with Databases (Postgres, SQL Server) and Data Platforms (Azure Databricks).
• Proven record of successful end-to-end data analysis project management: from problem and requirements definition to data validation and results presentation
• Proficiency with one or more enterprise Business Intelligence technologies (Power BI, Tableau, Spotfire)
• Solid understanding of Data modeling principles and design patterns.
• Proven experience building and operationalizing GenAI pipelines (Chunking, RAG, Vector index) on Databricks (Delta, Unity Catalog, MLflow, Jobs/Workflows, Spark, Lakeflow).
• Working knowledge of Microsoft Azure (storage, compute, identity/governance, Azure OpenAI).
• High level understanding of data engineering pipelines and data quality practices.
• Experience extracting/structuring data from unstructured sources (SOPs, reports, PDFs, ELN entries) using NLP or GenAI.
• Demonstrated experience in biotech/biopharma operations and partnering with SMEs across technical development, manufacturing, quality, or supply.
• Familiarity with Computer System Validation (CSV) documentation practices in regulated environments.
• Strong communication skills supporting collaboration across Technical Development, Manufacturing, Quality, and Supply Chain.

Who We Are
BioMarin is a global biotechnology company that relentlessly pursues bold science to translate genetic discoveries into new medicines that advance the future of human health.
Since our founding in 1997, we have applied our scientific expertise in understanding the underlying causes of genetic conditions to create transformative medicines, using a number of treatment modalities.
Using our unparalleled expertise in genetics and molecular biology, we develop medicines for patients with significant unmet medical need. We enlist the best of the best – people with the right technical expertise and a relentless drive to solve real problems – and create an environment that empowers our teams to pursue bold, innovative science. With this distinctive approach to drug discovery, we’ve produced a diverse pipeline of commercial, clinical and preclinical candidates that have well-understood biology and provide an opportunity to be first-to-market or offer a substantial benefit over existing therapeutic options.