Data Analyst and Investigation Engineer (biocompatibility)

Philips•Murrysville, PA

1d•Onsite

About The Position

Lead advanced scientific data analysis across biocompatibility and toxicological domains, synthesizing complex datasets spanning material science, laboratory studies, and regulatory inputs. Apply rigorous statistical methods (e.g., regression, DOE, reliability analysis) to generate defensible insights that support biological safety and product evaluation decisions. Design and operationalize scalable data infrastructure and analytical pipelines using SQL, Python, R, and related tools to ensure efficient data processing and reuse. Build automation workflows and maintain structured datasets that link materials, chemistry, biological endpoints, and reprocessing outcomes for consistent, end-to-end analysis. Develop and deliver data visualization and reporting solutions that translate complex scientific findings into clear, actionable insights for cross-functional stakeholders. Create dashboards, semantic models, and self-service tools that enable engineers, toxicologists, and regulatory teams to make informed, data-driven decisions. Support regulatory and quality-driven deliverables and validation activities, including BEPs, BERs, TRAs, and cleaning/disinfection assessments. Ensure all analytical outputs are traceable, reproducible, audit-ready, and aligned with quality system standards and documentation best practices. Drive data governance, security, and compliance across analytical systems and workflows, partnering closely with Information Security, Quality, and Regulatory teams. Enforce best practices in data handling, software validation, AI usage, and risk management while supporting secure deployment, monitoring, and remediation of analytical tools and platforms.

Requirements

2+ years of experience in data analytics.
Ability to analyze, interpret, and merge large datasets across multiple systems or platforms.
Proficiency in Excel with a demonstrated ability to perform advanced formulas & functions (VLOOKUP/XLOOKUP), pivot tables & data analysis, and data automation & workflow efficiency (macros/tools like Power Query).
Experience using Python (or similar languages) to develop tools for data manipulation and analysis.
Bachelor's or Master's Degree in an Engineering discipline, Data Analytics/Data Science or equivalent field of study.
Strong communication and teamwork skills.
Must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this position.

Nice To Haves

An understanding of SAP (or similar ERP).
Experience building dashboards with Power BI or Tableau.

Responsibilities

Lead advanced scientific data analysis across biocompatibility and toxicological domains.
Synthesize complex datasets spanning material science, laboratory studies, and regulatory inputs.
Apply rigorous statistical methods (e.g., regression, DOE, reliability analysis) to generate defensible insights.
Design and operationalize scalable data infrastructure and analytical pipelines using SQL, Python, R, and related tools.
Build automation workflows and maintain structured datasets.
Develop and deliver data visualization and reporting solutions.
Create dashboards, semantic models, and self-service tools.
Support regulatory and quality-driven deliverables and validation activities.
Ensure all analytical outputs are traceable, reproducible, audit-ready, and aligned with quality system standards.
Drive data governance, security, and compliance across analytical systems and workflows.
Enforce best practices in data handling, software validation, AI usage, and risk management.