Data Scientist, Workforce Staffing

Key Skills

Java Programming, Design, Python Programming, Framework, SQL, Agile methodologies, Machine learning techniques, Data science techniques, Business Intelligence, Deep Learning, Data Engineering, Mathematics, Large data sets, Data Analysis

Job Description

Amazon’s mission is to be the most customer centric company in the world. The Workforce Staffing organization is on the front line of that mission by hiring the hourly fulfilment associates who make that mission a reality. To drive the necessary growth and continued scale of Amazon’s associate needs within a constrained employment environment, Amazon is creating a Workforce Staffing Analytics program.

This program will re-invent how Amazon attracts, communicates with, and ultimately hires its hourly associates. This team will own multi-layered research and program implementation to drive deep learnings, process improvements, and strategic recommendations to global leadership. Are you passionate about data? Are you a tinkerer by trade? Do you enjoy questioning the status quo? Do complex and difficult challenges excite you? If yes, this may be the team for you.

As a Data Scientist in Workforce Staffing, your work is focused on research programs to deeply understand the people that make up our hourly workforce. You understand that even when hiring hundreds of thousands of hourly associates across multiple types of roles and businesses, the experience of each candidate matters.

You use your deep expertise in statistics (regressions, multilevel models, structural equation models, etc.), and data collection in a variety of settings (e.g., field studies, surveys, existing large data sets) to define and answer nebulous problems. You leverage your quantitative background to develop and test theoretical frameworks and design experiments. You design, deployment, and conduct analysis of our global candidate research activities, using experimental, quasi-experimental, and RCT methods. You relentlessly obsess over understanding our candidates and what attracts them to Amazon. You work with colleagues across Research, Data Science, Business Intelligence and related teams to enable Amazon find and hire the right candidates for the right roles at an unprecedented scale.

This will be a highly visible role across multiple key deliverables for our global organization. If you are passionate and curious about data, obsess over customers, love questioning the status quo, and want to make the world a better place, let’s chat.

Key job responsibilities

Working with hiring teams, business analysts, business intelligence engineers, data engineers, HR and operations colleagues to obsess about how to solve customer challenges with data. Using data to frame recommendations to business partners. Improving the status-quo of modelling and deployment techniques to reduce errors and improve trust in data.

BASIC QUALIFICATIONS

• A Bachelor or Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
• Three or more years in a research science, ML, or data scientist role and a track record of strong statistical analysis and building machine or deep learning models
• Experienced in using multiple statistical/data science methodologies to solve complex business problems.
• Strong background and experience using Python with handling large data sets using SQL in a business environment.
• Excellent verbal and written communication. Strong ability to interact, communicate, present, and influence within multiple levels of the organization

PREFERRED QUALIFICATIONS

• Master's or PhD in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least three years of working experience as a Data or Research Scientist.
• Experienced in writing academic-styled papers for presenting both the methodologies used and results for data science projects.
• Demonstrable track record of dealing well with ambiguity, ability to self-motivate, prioritizing needs, and delivering results in a dynamic environment.
• Combination of deep technical skills and business savvy to interface with all levels and disciplines within our and our customer’s organizations
• Experience in recruitment or operations

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