Sr. Data Scientist 1

BioMarin Pharmaceutical Inc.; Novato (CA); On-site; USD 170,000 - 230,000; Full time

Job summary

BioMarin Pharmaceutical Inc. seeks a senior Data Scientist in Technical Operations (TOPS) to advance end-to-end product lifecycle analytics with high-value AI solutions across Manufacturing, Quality, and Supply Chain.

You will own data strategy, apply ML/AI to complex regulated datasets, and collaborate with IT, engineering, and business SMEs to accelerate decision-making and drive process improvements.

Qualifications

• Master's degree in Data Science, Computer Science, Statistics, or related field with 7+ years delivering Data/AI solutions in industry.
• Advanced SQL and Python for data wrangling, feature engineering, modeling, and automation.
• Experience developing Python-based web apps using Dash, Flask, or Streamlit; familiarity with HTML/CSS and React is a plus.
• Strong experience with databases (Postgres, SQL Server) and data platforms (Azure Databricks).
• Proven end-to-end data analysis project management.

Responsibilities

• 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; participate in prioritization, planning, solution design, development, and deployment.
• Lead projects end-to-end with stakeholders; author business cases, designs, development and implementation documents.
• Advance Integrated Technical Data Strategy by defining roadmaps, value hypotheses, and success metrics.
• Acquire and prepare multi-source technical data ensuring quality, lineage, and context for AI development at scale.
• Engineer domain-aware features and reusable data assets for manufacturing, quality, and supply analytics.
• Build and validate ML/AI models for process monitoring, anomaly detection, and cycle-time optimization.
• Develop GenAI solutions (RAG, semantic search, Q&A) using enterprise platforms.
• Operationalize models with MLOps, pipelines, versioning, and drift monitoring.
• Collaborate with IT/Engineering to ensure scalable, secure AI services.
• Drive data visualization and dashboards to communicate insights to engineers and executives.
• Champion data integrity and documentation like model cards and validation records.
• Educate partners through demos, playbooks, and training to raise data/AI literacy.
• Quantify value realization and maintain a transparent AI initiative backlog.
• Promote build-first evaluations and contribute to TOPS AI standards.
• Stay current on AI advances and assess applicability to manufacturing and supply use cases.

Skills

Advanced SQL

Python

Data wrangling

Project management

Education

Master's in Data Science/CS/Statistics

Tools

Postgres

SQL Server

Azure Databricks

Dash/Flask/Streamlit

HTML/CSS/React

Job description

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.

About Technical Operations

TOPS acts as the critical link between Research & Development and Commercial Operations, integrating functions such as Technical Development, Manufacturing, Quality, Supply Chain, and Business Operations. Its teams maintain rigorous regulatory, quality, and safety standards while enabling seamless product advancement from development to market. The organization operates with a strong culture of learning, continuous improvement, and data driven decision making. Through data integration, analytics, and digital transformation initiatives, TOPS enhances process monitoring, deviation analysis, optimization, and strategic capacity planning, ensuring accurate and actionable technical data to support operational excellence.

Summary

The Data Scientist in Technical Operations (TOPS) plays a critical role in advancing BioMarin's end-to-end product lifecycle by delivering high value Data/AI Solutions across Technical Development, Manufacturing, Engineering, Quality, and Supply Chain functions. Data Scientists in TOPS contribute to owning, developing and executing the organization's Integrated Technical Data Strategy, applying advanced analytics, machine learning, and AI to complex datasets originating from Manufacturing, Quality and Supply Chain systems. They help transform fragmented data into actionable intelligence, extract insights which are otherwise hidden, identify gaps, and drive data maturity roadmap. This role blends advanced technical skills in Data Science-covering statistics, Modelling, AI/ML with deep domain expertise in highly regulated Biotech industry. These should be complemented by soft skills including collaboration, clear communication, presentation skills, enhanced clarity and ability to effectively translate those requirements to solutions. Data Scientists are expected to collaborate across departments, partners with Business SMEs, other Data Scientists/Analysts/Engineers and IT, and lead initiatives that promote a culture focused on decision science with an end-goal to help TOPS streamline operations, boost data reliability, and speed up decision-making.

Responsibilities

• 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.

Qualifications

Master's (minimum) in Data Science, Computer Science, Statistics, or related field; 7+ years of hands-on experience delivering Data/AI solutions in an industry setting.

• 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