Biomedical Engineer PAYS $66/HR Boston, MA

$137,280 - $137,280/Yr

Global Channel Management - Boston, MA

Full-time - Mid Level

Boston, MA

Administrative and Support Services

About the position

The Biomedical Engineer position at Global Channel Management, Inc. involves applying engineering principles to address challenges in biomedical signal processing, imaging, and physiological data interpretation. The role requires a strong background in biomedical engineering and data analysis, with a focus on developing and managing biomedical data solutions to support product development and clinical research.

Responsibilities

• Apply principles of biomedical engineering to solve problems related to signal processing, imaging, and physiological data interpretation.
• Ensure the quality, security, and scalability of biomedical data solutions.
• Perform exploratory data analysis and generate insights to inform product development and clinical research.
• Stay updated on emerging technologies and methodologies in biomedical data engineering and analytics.
• Assist in managing and setting up in-house evaluation tests, including scheduling sessions and monitoring participants.
• Manage the lab space and equipment, handling the shipping and receiving of numerous devices.
• Support data preparation and analysis for in-house evaluations and user acceptance tests (UATs).

Requirements

• Bachelor's or Master's degree or equivalent experience in Biomedical Engineering, Electrical Engineering, Mechanical Engineering or a related field.
• 6+ years' experience in biomedical engineering or a related field.
• Knowledge of cloud-based platforms (e.g., AWS, Azure, or Google Cloud).
• Strong understanding of biomedical signal processing and/or imaging technologies.
• Hands-on experience in analyzing biomedical data (e.g., ECG, accelerometer, PPG, or other physiological signals).
• Experience with the design and management of experiments with wearable sensors and human subjects.
• Familiarity with databases (SQL and NoSQL) and data management tools.
• Demonstrated experience in data engineering, including designing and managing ETL pipelines.
• Demonstrated experience in data analysis and visualization with Python and R, using frameworks and tools such as Pandas, NumPy, tidyverse, etc.