I’d like to share a job opportunity to pass on to your students and colleagues: to do survey statistics and uncertainty quantification for carbon credits in agriculture. We’re planning on using post-stratification techniques like those you used with Wei Wang. (Wei and I were interns together at Microsoft Research in 2013 when you did that super-cool study on Xbox users.)
Some background: I work at a Boston-based startup Indigo Ag. where we’re building a new program for carbon credits in agriculture. We’re crafting new methodologies with the Climate Action Reserve (California’s crediting body) and with Verra (the largest carbon registry) to quantify reductions in emissions thanks to adoption of regenerative land-management practices, such as cover crops, no-till, grazing, diverse crop rotations, and reductions in fertilizer.
My request: We’re looking to hire a statistician to supercharge our sampling and inferential methods for quantifying these carbon offsets across millions of acres. I would appreciate your sharing the job description with any students, postdocs, or other colleagues who might be interested. Also, this is a low-probability event, but let me know if you’d fancy doing consulting on applying statistics to create nature-based solutions to climate change. This area has a lot of fun statistical and mathematical problems to solve.