Senior Data Analyst Quality

Smith+Nephew•Minneapolis, MN

1d•Hybrid

About The Position

Life. Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living. As a Senior Data Analyst, you will play a pivotal role in turning complex Quality and Operations data into meaningful insights that drive compliance, product quality, and operational excellence. Working in a regulated medical device environment, this is an opportunity to influence decisions across the product lifecycle while supporting digital transformation and predictive quality initiatives. This is a US field based role with up to 10 percent travel.

Requirements

Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or a related technical field; a Master’s degree is preferred
2 to 5 years of experience in data analytics or an equivalent role
Strong analytical and statistical skills with proficiency in Python, R, and or SQL
Experience working with large datasets and querying complex data models
Proficiency with data visualization tools such as Power BI or Tableau
Familiarity with quality tools and methods including SPC, Six Sigma, and root cause analysis
Experience in a regulated industry such as medical devices, manufacturing, or logistics is preferred
Strong communication skills with the ability to present complex information to technical and non technical audiences
A continuous improvement mindset and the ability to work effectively both independently and as part of a team

Responsibilities

Apply statistical, analytical, and machine learning techniques to transform Quality and Operations data into actionable insights
Collect, clean, and analyze data from CAPA, complaints, nonconformances, and operational performance metrics
Identify trends, signals, and systemic quality risks using advanced analytical methods
Design, build, and maintain dashboards and KPI reports to support cross functional leadership and daily operations
Automate and optimize recurring Quality reports and analytics
Partner closely with Quality Engineering, Quality Systems, R&D, Manufacturing, IT OT, Regulatory, Operations, and Logistics teams
Support root cause analysis, risk assessment, audit readiness, and CAPA activities through data driven insights
Develop predictive and anomaly detection models for defect detection, process optimization, and productivity improvements
Document data workflows and business processes to ensure standardization, reproducibility, and compliance
Ensure all analytical approaches align with FDA QSR, ISO 13485, and internal Quality Management System requirements