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Fellow Product Performance Lead

Job in Arden Hills, Ramsey County, Minnesota, USA
Listing for: Boston Scientific
Full Time position
Listed on 2026-05-23
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Additional Location(s): N/A

At Boston Scientific, we give you the opportunity to harness all that's within you by working in teams of diverse, high‑performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information, and training, we help you advance your skills and career. Here, you will be supported in progressing toward whatever your ambitions.

About the role

We have an exciting opportunity for a Fellow Product Performance Lead within CRMDx Divisional Quality to provide technical leadership in the analysis and interpretation of product performance across the CRM portfolio. This role is responsible for leveraging post‑market data, advanced analytics, and cross‑functional collaboration to identify emerging risks, detect systemic trends, and generate actionable insights that drive awareness and decision‑making. As a key technical leader, the role operates at the intersection of product investigation, clinical insight, and risk management, translating complex data into clear, evidence‑based recommendations.

The Fellow will partner closely with Medical Safety, R&D, Design Assurance, and Manufacturing to ensure product performance insights are effectively integrated into decision‑making across the product lifecycle. This role will be hybrid out of the Arden Hills office, requiring you to be onsite at least three days a week.

Your responsibilities include:
Product Performance & Risk Insight
  • Leads the identification and interpretation of emerging product performance risks through deep expertise in the products, post‑market quality systems, product investigation, and industry best practices.
  • Integrates data across multiple domains—complaints, clinical, manufacturing—to assess system‑level performance and detect patterns that may not be visible through traditional monitoring.
  • Defines and evolves analytical frameworks, methodologies, and best practices for post‑market surveillance and signal detection, moving beyond traditional monitoring approaches.
  • Leads complex, high‑impact investigations requiring deep technical judgment and cross‑domain data integration.
Advanced Analytics & Signal Detection
  • Applies advanced analytical, statistical, and hypothesis‑driven methods to identify weak signals and emerging trends across high‑volume, multi‑source data.
  • Leverages predictive analysis, pattern recognition, and data modeling techniques to anticipate potential product performance issues.
Technical Judgment & Decision Influence
  • Provides independent, evidence‑based evaluation of product performance trends and monitoring strategies.
  • Translates highly complex data into clear, defensible, and actionable insights for technical and business stakeholders.
  • Influences product, risk, and design decisions through clear, data‑driven insight in cross‑functional forums across R&D, Quality, Medical Safety, and Manufacturing.
  • Serves as a key voice in risk evaluation, product design discussions, and quality strategy forums.
Cross‑Functional Leadership & Influence
  • Serves as the technical lead across Quality, Medical Safety, R&D, and Manufacturing to align on product performance insights and emerging risks.
  • Drives data‑informed decision‑making in high‑visibility and time‑sensitive situations with cross‑functional partners to ensure appropriate understanding and evaluation so that decisions across design, risk, and quality are supported.
Process & Capability Development
  • Evaluates the effectiveness of current signal detection and monitoring processes and drives continuous improvement.
  • Establishes scalable, repeatable, and measurable frameworks for product performance monitoring.
  • Partners with data science and technology teams to define requirements and implement AI/ML analytical tools.
Required Qualifications
  • Minimum of a Bachelor's degree in Engineering or related fields.
  • Minimum of 10 years of experience in implantable medical devices with an emphasis in cardiac pacing, defibrillation, or diagnostic therapies and technologies.
  • Demonstrated expertise in analyzing complex, multi‑source data to drive technical conclusions and translate into actionable recommendations.
  • Proven ability to…
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