Applied Scientist, Machine Learning - PeopleScience

Job description

DESCRIPTION

The Team
The PeopleScience (PS) team is a science team that supports Amazon Connections for WW Ops and creates innovative products that can be used in WW Operations to enhance the employee experience and develop leaders. Examples of projects we own include Engagement Index (EI) which provides leaders with a pulse on employee engagement in their orgs, Safety Leadership Index (SLI) which provides perceptions of safety sentiment to building leaders in CF and Recommendations, a product that provides messages and tips to frontline leaders in CF and CS to enable their development based on how their teams respond to “manager” questions asked through Connections. The team is comprised of Research scientists, Data Scientists, BIEs and Product managers. Candidates will need to be comfortable operating quickly and autonomously, strike the right balance between speed and scope, and display strong ownership to pick up any work that gets deliverables across the line.

The Role
This Applied Scientist will be responsible taking Connections questions to the next level by building an intelligent deep dive system that automatically conducts deep dives into area of employee concern using statistical models, ML techniques, or other data-driven technical solutions. Deep experience applying a breadth of statistical/ML classification and regression techniques is required. In addition, this scientist will be responsible for personalizing our recommendations product to ensure managers receive the right messages at the right time. The successful candidate will have experience working cross-functionally where both science and technology converges to formalize problem definitions from ambiguous requirements, work with multiple teams in other orgs and take the Connections research and products to the next level. This Applied Scientist will build and deploy their own code to production (using scripting languages like Python/R), so they must meet technical bar to be able to partner effectively with SDEs and Data Engineers. A pure academic is not what we are looking for.

Being successful on this team requires the ability to:
· Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key features and processes
· Work closely with software engineering teams to drive new feature creation
· Work closely with stakeholders to optimize various business operations
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
· Track general business activity and provide clear, compelling management reporting on a regular basis
· Research and implement novel statistical approaches

Desired profile

BASIC QUALIFICATIONS

· M.S. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 1+ years of hands-on experience in predictive modeling and analysis
· Evidence of passing SDE1 coding bar at Amazon
· Strong algorithm development experience
· Skills with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language