Senior Data Scientist – Medical Device (Post-Market & Risk Analytics)

Location: Remote (PST)

Position Overview

We are seeking an experienced Senior Data Scientist to support advanced analytics initiatives across post-market surveillance, manufacturing, supplier quality, and product design within a regulated medical device environment.

This role focuses on identifying systemic failure patterns, conducting root cause analysis, and delivering data-driven insights to improve product reliability and reduce operational risk.

Key Responsibilities

• Analyze and correlate post-market data (e.g., complaints, product usage, field performance) with:

  • Manufacturing processes
  • Supplier quality metrics
  • Product design factors

• Identify failure trends and translate findings into actionable recommendations

• Lead end-to-end root cause analysis using both structured and unstructured data

• Develop and apply machine learning and statistical models to detect patterns and risks

• Work with unstructured data (e.g., text, product usage, or behavioral data) to extract insights

• Deliver proactive analytics to support:

  • Risk detection
  • Product quality improvements
  • Operational decision-making

• Partner closely with cross-functional teams including engineering, quality, manufacturing, and business stakeholders

• Support audit readiness and data-driven regulatory initiatives

Required Qualifications

• 7+ years of experience in data science, machine learning, or advanced analytics
• 3+ years of experience within medical device or regulated manufacturing environments
  (non-clinical; must be product, quality, or post-market focused)
• Strong understanding of quality systems, regulatory expectations, or post-market processes

Core Technical Skills

• Advanced Statistics

  • Statistical modeling, hypothesis testing, experimental design

• Machine Learning / Analytics

  • Predictive modeling, clustering, classification

• Data Platforms

  • Experience working in Databricks or similar big data environments
  • Strong SQL and data processing skills (Spark/PySpark preferred)

• Data Handling

  • Experience working with large-scale and unstructured datasets

Domain Experience (Required – Medical Device)

• Post-market surveillance and complaint data analysis
• Root cause investigation and failure analysis
• Product quality and design-related analytics
• Operational risk analysis and trend identification

Nice to Have

• Experience with SAP or manufacturing/quality data systems
• Exposure to supplier quality or production data
• Experience with NLP or text analytics