Staff Electrical Engineer (Research and Development)
WHOOP
Requirements Educational Background: BS or higher in Electrical Engineering, Computer Science, Mathematics, Statistics, or a related field
- Experience: 7+ years of experience
- Problem-Solving Expertise: Strong ability to apply data analytics to solve complex engineering challenges and propose creative, data-driven solutions
- Statistical Skills: Proficiency in applying advanced statistical techniques, particularly in time-series data analysis, using Python or similar tools (e.g., Minitab)
- Hands-On Engineering: Experience with hardware prototyping and debugging, utilizing lab equipment such as oscilloscopes, multimeters, and impedance analyzers
- Circuit Design Expertise: Solid understanding of circuit design principles
- Software & Code Management: Experience maintaining and improving live code for hardware systems, including logging, monitoring, and debugging in development environments
- The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office
- Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply
- Our hardware team thrives on rapid prototyping and data-driven insights, so hands-on experimentation and a keen ability to extract meaningful conclusions from complex datasets are essential. If you're passionate about using data to shape the future of wearable technology, we want you on our team
- Advanced Development Projects: Spearhead early-stage design and development of biometric wearable devices, using data analytics to guide decision-making and determine success criteria
- Data-Driven System Validation: Design and execute system-level validation protocols, utilizing engineering fundamentals combined with statistical methods to ensure optimal performance in real-world scenarios
- Advanced Data Processing & Statistical Techniques: Use Python and other statistical tools to process large data sets, conduct feasibility testing, and inform engineering design decisions
- Circuit Design & Simulation: Apply an understanding of circuit design principles and tools like SPICE for designing and validating hardware circuits in wearable technology systems
- Prototyping & Functional Verification: Test and validate hardware prototypes for in-depth functional testing, utilizing a variety of lab equipment for debugging and analysis
- Test Design & Failure Investigation: Define system requirements and develop test strategies, analyzing test data to ensure validation. Lead failure investigations using data to identify root causes and improve designs
- Cross-Functional Collaboration: Partner with teams across hardware, software, data science, and product to shape development strategies, ensuring data insights drive both technical and strategic decisions
- Stakeholder Engagement: Collaborate with external partners, suppliers, and contract manufacturers to ensure successful development and scale-up of products
Vacancy posted 1 day ago
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