Senior Biomedical Engineer

Key Skills

Biomedical Imaging, Data Analysis, Data pipelines, Database, JMP, Machine learning techniques, MATLAB Programming, Python Programming, Signal processing

Job Description

A Day in the Life 

The Senior Biomedical Engineer will provide technical leadership through competencies in biosensing, medical device processes, and mathematical modeling. The focus will be on characterization of input to output relationships of biosensor design, manufacturing processes, and signals as well as the application of models for design and process development. This individual will conduct rigorous experimentation, data processing, and modeling to characterize systems. There will be strong emphasis on data analysis best practices, statistical and mathematical modeling methodologies, Design for Reliability and Manufacturability (DRM) principles, and application rigor. This individual will conduct experimentation, analysis, and simulation to generate quality results, providing development guidance and providing decisions to advance sensor programs.

This individual will be expected to perform independently and is responsible for model building, data analysis, collaborating within and across functions, project management, and writing technical documentation. There will be occasions when communication to upper management is required through presentations and reports, and the individual must have the ability to effectively convey technical updates to internal and external stakeholders.

Specific Responsibilities include:

• Contributing member within multidisciplinary teams to support the development of next generation subcutaneous biosensors with emphasis on glucose sensing
• Analysis and understanding of sensing modalities, processes, and system integration 
• Conducting experiments (ex. DOE) to model sensor performance output variability and main effects 
• Apply data management best practices for building data pipelines and collaboration
• Apply & instill Best-Known-Methods for statistical and mathematical modeling of sensor systems
• Apply and interpret characterization models to establish optimal feature set points with respect to sensor in-vivo performance
• Provide guidance to development programs through the application of analysis and model insights and outcomes
• Assume responsibility as subject matter expert to represent organization as primary contact for specific projects and initiatives
• Utilize technical skills associated with Six Sigma, Lean, DRM/DFSS and other appropriate continuous improvement techniques
• Ensure execution of detailed engineering analyses & documentation to support design development and support process transfer
• Work with other engineers and technicians to execute experimental designs and analysis

Must Have: Minimum Requirements 

To be considered for this role, please ensure the minimum requirements are evident in your applicant profile. 

• Bachelors of Science in Biomedical Engineering, Chemical Engineering, Engineering, Computer Science or related sciences and 4+ years experience in product design, scientific research or engineering experience.

OR

• Advanced Degree in Biomedical Engineering, Chemical Engineering, Engineering, Computer Science or related sciences and 2+ years experience in product design, scientific research or engineering experience.

Nice to Have

• Medical Device Industry Experience
• Demonstrated knowledge of biosensing fundamentals and signals
• Experience with statistical analysis of data (Ex. Minitab, JMP, Matlab, etc.)
• Direct experience in characterization, design of experiments (DOE) and data analysis methodologies
• Experience in developing statistical and mathematical models
• Experience with technical documentation (Ex. laboratory notebooks, publications, engineering reports, specifications, validations, Standard Operating Procedures, test protocols, etc.)
• Direct experience with MATLAB and/or Python
• Experience with advanced statistical analysis techniques (regression, factor, cluster, etc.)
• Experience with machine learning
• Experience in signal processing, interpretation, and analysis of biosensing signals
• Experience with databases and building data pipelines
• Experience applying model simulation for solution optimization
• Exposure to DMAIC or equivalent Scientific Method problem solving for root cause analysis efforts
• Direct experience in manufacturing process development
• Knowledge of analytical instruments and methods
• Knowledge about in-vitro and in-vivo testing of subcutaneous medical devices
• Experience with Project Management and relevant tools
• Knowledge of medical device product development cycle
• Related experience providing supporting data to governing bodies (FDA, cFDA, PMDA, LNE GMED, etc)