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Mathematica · 2 days ago

Quantitative Researcher (Education & Employment) (Remote Eligible)

United States

Full-time

Remote

Mid, Senior Level

$100K/yr - $135K/yr

Mathematica is a company that applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. They are seeking a quantitative researcher to support rigorous, data-driven, evidence-building activities in the areas of employment, education, and disability.

Research

Culture & Values

No H1B

Security Clearance Required

Responsibilities

Participating in evaluation activities such as developing rigorous study designs, analyzing quantitative data from surveys and administrative sources, reviewing and synthesizing existing evidence, applying innovative methods such as machine-learning techniques, contributing to briefs and reports, and developing data visualizations to enhance the accessibility of findings

Helping program administrators and policymakers make decisions by cleaning, organizing, analyzing, and presenting large amounts of data

Assessing the strength of study designs and summarizing large and diverse sets of existing research through systematic reviews and meta-analyses

Guiding program staff and policymakers in the use of evidence to make decisions about program selection and adaptation

Collaborating with state and local organizations through conducting evaluations or refining their programs

Presenting findings and disseminating information to policy, practitioner, and researcher audiences

Qualification

Quantitative research methodsCausal inferenceData analysisR programmingPython programmingSTATA programmingWritten communicationOral communicationTeamwork

Required

Ph.D. in economics, public policy, sociology, education, statistics, data science/data analytics, or a related field. In lieu of a PhD, a Masters' degree with coursework in causal inference and demonstrated experience applying it to research will be considered equivalent

Strong quantitative analytical skills, including training in causal inference methodologies

Experience working with programming languages such as R, Python, or STATA

Excellent written and oral communication skills, including an ability to translate complex research methods and findings for a practitioner and policy audience

Ability to work well in teams