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Digital Product Manager

Job in Beaverton, Washington County, Oregon, 97078, USA
Listing for: Insight Global
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
  • Bachelor’s or Master’s in Engineering, Data Science, Kinesiology/Biomechanics, Computer Science, Human Performance, or related field.
  • 10+ years of experience in research data workflows, digital product management, or data platform technical program management.
  • Proven ability to map complex processes and produce clear technical documentation.
  • Experience partnering with data engineers, analysts, or data platform teams.
  • Strong understanding of metadata standards, data quality methods, and version‑control practices.
  • Excellent communication skills across technical and non‑technical teams.
Nice to Have Skills & Experience
  • Familiarity with sensor‑based research (motion capture, IMU, EMG, force plates) and time series data.
  • Knowledge of biomechanics workflows (kinematics, kinetics, filtering, inverse dynamics) or markerless motion capture.
  • Experience in innovation labs, applied sports science, or product creation environments.
  • Comfort interpreting Python, MATLAB, or R analysis logic.
  • Experience with LIMS/ELN systems or structured research‑data platforms.
  • Background creating SOPs, data contracts, and process maps.
  • Strong technical literacy in device design, hardware‑software integrations and digital ecosystems
Job Description

The largest footwear retailer headquartered in Beaverton, OR is hiring for a Digital Product Manager to join their team. This role will be partnering closely with researchers, data engineers, analysts, and platform partners to develop and deliver advanced digital concepts and solutions for data related workflows.

This role defines data requirements, maps and optimizes research workflows, and ensures that the end‑to‑end data ecosystem—from collection through analysis‑ready outputs—supports scalable, high‑quality scientific work.

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