Data Scientist - WW Operations HR

Job ID: 1160667 | Amazon.com Services LLC

DESCRIPTION

Amazon delights millions of customers around the world. Meet PI-Squared, the behind-the-scenes team, that enables our HR and Operations Leaders to make informed decisions and improve the overall experience of a million frontline employees and leaders throughout their journey at Amazon. Our diverse team of statisticians, machine learning experts, and social scientists strive to make Amazon HR the most scientific HR organization in the world. We form hypotheses about the best talent acquisition, talent retention, and talent development techniques, and then set out to prove or disprove them with experiments and careful data collection.

The ambition of Amazon HR is to be the most scientific organization in the world. We bring data and machine learning into management science to deliver workforce, associate experience, and leadership insights so Amazon leaders can focus their efforts in ways that will engage, retain and grow their talents. You will have the opportunity to work with operation leaders across different business lines to gain deep insights into Amazons’ daily operation and directly impact productivity, quality, and safety of hundreds of thousands of employees’ everyday life.

Roles and Responsibilities:
(1) Undertake econometric / statistical analysis to measure impact of various initiatives in the HR space.
(2) Design and measure experiments
(3) Undertake qualitative analysis to augment the findings from quantitative studies
(4) Build scalable analytic solutions using state of the art tools based on large datasets

This role requires an individual with strong quantitative modeling skills and the ability to apply statistical/machine learning, econometric, and experimental design methods. Preference will be given to candidates with additional experience in qualitative analysis in a variety of settings such as focus groups, field studies, surveys, and observational studies.

The ideal candidate will be:
· A Well-Rounded Athlete –Like a true athlete, you understand that we succeed or fail as a team. You are always ready to step up beyond your core responsibilities and go the extra mile for the project and your team. You nimbly overcome barriers to deliver the best products more quickly than expected.
· A Perpetual Student – You seek knowledge and insight. You challenge yourself to turn moments into master’s classes. Whether closing a gap, developing a new skill, or staying ahead of your industry, you revel in the joy of learning and growing.
· A Skilled Communicator – You excel when interacting with business and technical partners whether you are chatting, sending a written message, or conducting a presentation.
· A Trusted Advisor – You work closely with stakeholders to define key business needs and deliver on commitments. You enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format.
· An Inventor at Heart – You innovate on behalf of your customer by proactively implementing improvements, enhancements, and customizations. Your customers marvel at your creative solutions to challenges they had not yet identified.
· A Fearless Explorer – You are drawn to take on the hardest problems, navigate ambiguity, and battle skepticism. You never settle, even in the face of overwhelming obstacles.


BASIC QUALIFICATIONS

· PhD in Statistics, Economics or closely related field.
· Experience in SQL, R, Python, or another scripting language; command line usage
· 2+ years of industry research experience, with a strong portfolio that illustrates how your research informed decision-making
· Excellent written and verbal communication skills for both technical and non-technical audiences
· Experience with analyzing large datasets
· Ability to engage business partners and stakeholders and solve an ambiguous business problems with appropriate choice of data science solutions

PREFERRED QUALIFICATIONS

·
· Previous experience in a ML or data scientist role with a large technology company
· Familiarity with Time Series Analysis and/or Predictive Modeling techniques
· Prior well-established recognized academic experience, multiple publications in top-tier academic journals
· Familiar with machine learning tools and data infrastructure in Amazon Web Service
· Previous experience in a science role with a large technology or consumer company