Workforce Staffing (WFS), a division of Amazon’s Worldwide Operations Human Resources, manages Amazon’s Tier 1 talent supply chain. We attract, hire, and onboard the associates who, by fulfilling orders at the frontlines of the company, make Amazon a global leader in delivery and logistics. The mission of the Candidate Experience Research Team (CER) is to drive positive change to Workforce Staffing’s hiring and onboarding experience. We conduct research and analyses on opportunities and successes for the business, and develop products that amplify the voice of our candidates.
We are seeking a manager, data science, with a heavy focus on quantitative data analysis and evaluation, and a deep focus on understanding labor markets. You will be responsible for building a new team from the ground up, develop roadmaps, and drive business impact through your research at global scale.
The ideal candidate should be well versed in quantitative methods, including classical statistics and machine learning approaches. Competitive candidates will be very comfortable with at least one computational language (e.g., R, Python). Candidates should be comfortable combing through computational models, machine learning algorithms, and analyzing their output.
Candidates should have demonstrated experience leading data science projects related to labor market research and analysis, including research on wage sensitivity and elasticity, workforce relevance, and other factors.
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 Workforce Staffing matches talent to business demand.
This role will be located in Nashville.
If you’re hungry to engage and empower Amazon Associates your expertise in mixed methods research, let's talk.
· Master’s degree in a relevant quantitative discipline
· Experience independently designing and executing research or evaluations aimed at answering ambiguous, difficult-to-test questions
· Comfortable with at least one computational language (e.g., R, Python)
· Experience building and managing teams
· 4+ years of post-academic experience
· 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
· Demonstrated written and verbal communication skills
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.