Senior Scientist

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Requirements:

• PhD (or equivalent research experience) in atmospheric science, climate physics, aerosol chemistry, or a related field.
• 8+ years leading interdisciplinary research projects that mix field, lab, or modeling work.
• Demonstrated strength in experimental design, uncertainty analysis, and handling large environmental datasets with Python, R, Julia, or MATLAB.
• You’re an exceptionally fast learner. You enjoy (and have experience) quickly ramping on new technical topics.
• You have excellent oral and written communication skills - and in particular, you are adept at translating technical jargon into layman’s terms and summarizing complex concepts in a succinct manner.
• You have excellent quantitative skills, including experience analyzing the cost- and feasibility-drivers of experimental designs
• You’re uniquely good at getting to the crux of an issue, and can quickly sort the signal from the noise
• You’re creative and attached to outcomes, not process – you’re constantly looking for new paths to the destination and excited to switch gears if there’s a faster, better way to get something done.
• You are low ego, and have a proven track record for working well across teams and with external partners

Responsibilities:

• Roadmap delivery – break priority questions into fundable work packages, set quarterly goals, and flag bottlenecks early so we can adapt quickly.
• Uncertainty tracking – maintain a living “uncertainty and risk database” that shows what we don’t yet know, why it matters, and who is best placed to close each gap.
• Technical diligence – review proposals and provide clear, budget-aware recommendations.
• Network building – Build and maintain high-trust relationships across academia, government labs, and industry – including researchers we’ve funded and those we haven’t – so that we know who to turn to for needed expertise.
• Knowledge synthesis – Write concise memos and public explainers that translate technical results into next-step decisions for Reflective and the wider community.
• Internal projects – Scope and occasionally run short in-house projects when external capacity is missing, coordinating closely with our engineering and data teams.