Sr. Quality System Data Specialist

Getinge•Wayne, NJ

9d•$105,000 - $130,000•Remote

About The Position

The Sr. Quality Data & Analytics Specialist is responsible for transforming data into meaningful insights that support product quality, patient safety, regulatory compliance, and operational excellence within global Getinge. This role combines expertise in statistical analysis, data analytics, artificial intelligence (AI), and data integration to support businesses with pro-active signal detection, reducing patient risk. The Senior Specialist will work closely with Legal Manufacturers, Quality, Regulatory Affairs, Medical Safety, Service, Manufacturing, and Information Technology teams to develop methods and tools to identify trends, detect emerging signals, automate manual processes, and provide actionable insights that support data-driven decision making. This position is ideal for an analytical professional who enjoys solving complex problems, leveraging modern analytics and artificial intelligence (AI) tools, and helping business partners make informed decisions using data.

Requirements

Bachelor’s or Master’s Degree in a relevant field (e.g., statistics, data science, biostatistics, mathematics, or equivalent combination of education and experience is required).
A minimum of 5 years relevant experience in the following fields:
Experience in one or more of the following areas is preferred: data analytics, data science, medical device quality, healthcare analytics, statistical techniques
Solid knowledge and application of Descriptive statistics, Statistical trend analysis, Hypothesis testing, Risk-based monitoring, Data visualization techniques
Ability to interpret complex datasets, support identification of meaningful trends and signals, & communicate statistics concepts clearly.
Problem solver & critical thinker with attention to detail
Understanding of Generative AI, Large Language Models (LLMs), Machine Learning fundamentals
Natural Language Processing (NLP), Predictive analytics, Data automation tools, Responsible AI principles
Ability to identify practical applications of AI that improve processes and efficiency.
Curiosity for emerging technologies and analytical methods, continuous improvement mindset
Ability to communicate effectively
Demonstrate ability to work collaboratively in a cross-functional environment.
Experience with one of more of the following applications: Power BI, Tableau, SQL , Python, R, Microsoft Fabric, Databricks, Snowflake, Azure analytics tools, Microsoft Copilot or similar AI platforms

Responsibilities

Act as a Subject Matter Expert in Statistical methods, supporting legal manufacturers with selection of appropriate statistical methodologies (when needed) to evaluate product performance and quality indicators.
Develop and implement dashboards, scorecards, and visualizations supporting analyses to identify trends, patterns, anomalies, and emerging signals within quality and post-market data.
Continuously improve insights of dashboards, scorecards and visualizations utilizing data from multiple business systems and tools and other sources. Design output to support action determination.
Present complex analytical findings in a manner understandable to both technical and non-technical audiences.
Support management reviews and quality performance reporting activities.
Identify opportunities to leverage AI and automation to improve the efficiency and effectiveness of signal detection, including trend analysis, data extraction, process automation, and knowledge management.
Evaluate emerging AI technologies and recommend practical business applications.
Support implementation, testing, validation, and monitoring of AI-enabled solutions.
Follow and help establish best practices for responsible and effective use of AI within regulated business processes.
Work with data from multiple sources, including Complaint handling systems, CAPA systems, ERP systems, Service databases, Manufacturing systems (e.g. NCR), Customer feedback systems
Identify opportunities to improve data quality, accessibility, and usability.
Collaborate with IT and stakeholders to improve data connectivity and analytics capabilities.
Assist in developing data models and reporting structures that support business needs.
Partner with Legal Manufacturers and functional stakeholders to understand business questions and analytics needs.
Support quality and regulatory initiatives through data-driven analyses.
Participate in continuous improvement projects focused on quality system effectiveness.
Act as a trusted resource for analytics, statistical interpretation, and AI-related opportunities.
Provide training and guidance to business partners on data interpretation and dashboard utilization.