Collecting high quality data is a critical component of STEM research and evaluations, and it is central to stand-alone national surveys used to provide up-to-date statistics to enable researchers and policymakers to monitor the size and characteristics of the scientific workforce.
Evidence & Insights

How Machine Learning Streamlines the Occupational Coding Process for a Survey of Doctorate Recipients
The information collected from the Survey of Doctorate Recipients (SDR) provides statistics on the nation’s doctoral scientists and engineers that enable researchers and policymakers to monitor their career movement as well as the size and characteristics of the scientific workforce.
Learn moreProgress is best made together.
Partner with us at the intersection of data science, social science, and technology to progress from inquiry to insight to impact. Our evidence-informed solutions empower you to see clearly and act quickly.
Efficiency Meets Impact.
That's Progress Together.
Mathematica delivers evidence-based solutions to optimize programs and policies for efficiency, cost savings, and measurable impact. Learn more about becoming a client or partner.
Work With Us