Principal Scientist, Process Engineer - Burt’s Bees
- Be the technical leader and subject matter expert on scale-up readiness and manufacturing feasibility across the full Burt’s Bees product portfolio
- Independently lead complex technical programs and collaborate cross-functionally to drive a suite of projects
- Manage pilot plant operations and capital investments to enable scalable, future-ready technical capabilities
- Actively scout and integrate external technologies and manufacturing innovations to build and strengthen internal capabilities
- Translate business strategy into actionable technical Process solutions, connecting long-term goals to smart, scalable solutions.
- Establish, author, and maintain best practices and standards for scale-up, ensuring safety, compliance, and technical rigor
- Lead with impact, taking ownership of technical talent growth through coaching, skill-building, and fostering a culture of continuous improvement.
- Champion and drive improvements in cost, sustainability, and operational efficiency in close collaboration with manufacturing partners.
- Apply data-driven approaches to inform decisions and optimize processes.
- Bachelor’s degree from an accredited institution in Engineering required.
- Minimum 8 years of deep experience in Process Development and scale-up in personal care consumer products or adjacent regulated environments (i.e. OTC, Food, etc.).
- Change-makers who lead with action: spotting opportunities, taking initiative, and moving quickly to create meaningful impact.
- Inspiring and strategic builders, raising the bar on technical excellence and empowering teams through hands-on leadership.
- Strong technical curiosity, critical thinking, and creative problem-solving skills with a record of implemented innovative and effective technical solutions.
- Champions of safety, compliance, and scientific integrity – creating space for learning while driving adoption of new tools, processes, and programs.
- Demonstrated experience in applying Design of Experiments (DoE) and statistical analysis tools (ex: JMP) to optimize and validate processes.
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