Mixed Methods Research Scientist

US, WA, Virtual Location - Washington

Applications have closed
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Posted 3 months ago

In Customer Trust and Partner Support (CTPS), thousands of Amazonians spend their days obsessing over how to continually provide a safe and trustworthy store for our customers, brands, and selling partners. In this rich, demanding environment, it is vital that we invest significant effort to hire and develop the best.

How do we do this effectively? That’s where you come in. Help us build a brand new core research team focused on talent growth and retention.
We are seeking a mixed-methods researcher with deep expertise in social science, public health, or similar research, including development and evaluation of theoretical frameworks, qualitative data collection and analysis methods in a variety of settings (e.g. focus groups, field studies, surveys, observational studies, “found data”, quantitative analytics), and statistics (t-test, ANOVAs, regressions, etc.). The ideal candidate will be equally comfortable with qualitative and quantitative methods, though candidates with greater exposure to and familiarity with qualitative methods will be considered if a solid understanding of the quantitative methods described above exists.
You will be responsible for spearheading research that leverages both qualitative and quantitative methods to understand and improve how CTPS attracts, hires, and retains talent of the highest caliber. Our approaches are driven by our research questions, so you should be comfortable with various mixed-methods research designs, both concurrent and sequential. Additionally, you should be comfortable with making independent decisions about qualitative study conduct, including determinations of sample size/saturation, purposive sampling, and close monitoring of data quality (including primary responsibility for code book development, coding procedures, and data validation).
A customer-obsessed, relentless curiosity is a must, as is commitment to the highest standards of methodological rigor that a given study allows. This role provides opportunity for significant exposure to Amazon’s culture, leadership, and global businesses, and furthermore provides significant opportunity to influence how CTPS hires and develops the best.

If you’re hungry to engage and empower Amazonians with your expertise in mixed methods research, let's talk.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Basic Qualifications

· Master’s degree in a discipline of social science (sociology, anthropology, social work, education, etc), public health, or a closely related field
· Experience independently designing and executing research or evaluations aimed at answering ambiguous, difficult-to-test questions using mixed methods
· Experience using qualitative research tools (e.g. MAXQDA, NVivo, Atlas.ti, Dedoose) and quantitative tools (e.g. SPSS)
· At minimum, working knowledge of quantitative approaches (e.g., t-tests, regressions, ANOVAs, etc.)
· Proven written and verbal communication skills
· 2+ years of post-academic experience

Preferred Qualifications

· Ph.D. in a discipline of social science (sociology, anthropology, social work, education, etc.).
· Experience converting research studies into tangible real-world changes
· Experience navigating conflicting priorities and ambiguous problems
· Experience communicating qualitative research methods and findings to non-qualitative researchers
· Demonstrated experience conveying complex subject matter to clients and stakeholders
· Demonstrated ability mentoring, coaching, and influencing colleagues, collaborators, and stakeholders
· Working knowledge of R or Python
· Demonstrated deep knowledge of and experience with qualitative research methods

Job tags: Coaching Mentoring Python R Research Statistics