Applied Scientist, AWS Workforce Planning Science

Key Skills

C Programming, C# Programming, C++, Java Programming, MATLAB Programming, Python Programming, R Programming, SAS, SQL

Job Description

Job summary

The AWS Workforce Planning team has an exciting opportunity for an Applied Scientist to join the team that owns the science behind AWS HR products, programs, and metrics.

We come up with innovative ways to use econometrics, machine learning, and statistics to improve the experience of AWS employees and to help HR/recruiters put the right people in the right place at the right time to staff all of AWS.

Key job responsibilities

• Build state of the art scientific models to predict employee headcount and movements across all Amazon businesses
• Design and implement experiments, simulations and mechanisms to quantify the impact of policy changes on talent movement
• Build models to understand drivers of promotion, attrition, transfers, and hires
• Identify and work with external and internal talent data-sets and develop ways to combine the two to answer important talent research questions
• Work with other scientists, Data Engineers, and SDEs on the team to scale solutions that have a strong business impact

About the team

The AWS Workforce Planning Product, Engineering and Science team has the mission to put the right people in the right place at the right time to staff all of AWS, building scalable and robust software solutions that plan the AWS workforce and support execution to plan.

We harness economics, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of product, science and engineering to develop and deliver solutions that measurably achieve this goal.

BASIC QUALIFICATIONS

• Masters degree in Statistics, Economics, Finance, Computer Science, Mathematics, Operational Research, Engineering or a related discipline
• 2+ years of experience in predictive modeling and analytics.
• 2+ year of experience with Python, R, MATLAB or similar scripting language.
• Experience with SQL and statistical computing tools.
• Experience in algorithm development.
• Experience in applying theoretical models in an applied environment.

PREFERRED QUALIFICATIONS

• Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 2+ years of research or work experience as an Applied Scientist, Data Scientist, Software Engineer, or a related occupation.
• Strong verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
• 2+ years of research or work experience in programming with a mathematical programming language such as R, MATLAB, or SAS or major programming language such as Python, Java, C++, C#, or C
• Extensive experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems.