Data Scientist

Job description

DESCRIPTION

Amazon delights millions of customers around the world. Meet the behind the scenes team that enables our Human Resource and Operations Leaders to make informed decisions. The Amazon PeopleInsight team builds reporting and analytics tools for our teams that fulfill customer promise every day. Whether it is Fulfillment Center team that delivers your Prime order in two days, our Amazon Locker team that lets you pick up your package anytime that is convenient for you, our Prime Now team getting you lunch in under an hour, or one of many more, the PeopleInsight group is there providing people metrics along the employee lifecycle for our global operations businesses. The PeopleInsight team is a collaborative group of Business Analysts, Business Intelligence Engineers, Data Engineers, Data Scientists, Product Managers, and Program Managers dedicated to empowering leaders and enabling action through data and science. We deliver workforce, associate experience, and leadership insights so Amazon leaders can focus their efforts in ways that will engage, retain and grow their associates.

We are now recruiting for an exceptional Data Scientist, Worldwide Operations

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.

Roles and Responsibilities
Success in this role will include influencing within your team and mentoring peers. The problems you will consider will be difficult to solve and often require a range of data science methodologies combined with subject matter expertise. You will need to be capable of gathering and using complex data set across domains. You will deliver artifacts on medium size projects, define the methodology, and own the analysis. Your findings will affect important business decisions. Solutions are testable and reproducible. You will create documents and share findings in line with scientific best practices for both technical and nontechnical audiences.

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

Desired profile

BASIC QUALIFICATIONS

· Masters with two years of experience or a Bachelors with five years of experience.
· Experience in SQL, R, Python, or another scripting language; command line usage
· Track record of diving into data to discover hidden patterns and of conducting error/deviation analysis
· Knowledge of various machine learning techniques and key parameters that affect their performance
· Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations
· Evidence of using of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects
· Excellent written and verbal communication skills for both technical and non-technical audiences