Company Name:-
Amazon.com Services LLC

Job Location:-
Seattle, WA

Job Summary:-
Job detailsJob TypeFull-timeFull Job DescriptionPhD/M.

S.

in Computer Science, Machine Learning, Operational Research, Statistics, or a related quantitative field
At least 5+ years of hands-on experience in developing and applying models in a production environment
Strong software design, coding, problem solving, and complexity analysis
Experience programming in Python, R, Spark or related lang

Do you want to reinvent HR on a cross-functional incubation team? Are you passionate about using science to build disruptive solutions that challenge status-quo? Do you want to fundamentally redefine talent management for one of the largest and most complex workforces in the world? If you are, we want to talk to you.

A day in the life
As a Senior Applied Scientist, you will leverage data, customer feedback, algorithm design, machine learning, econometrics, and predictive analytics to “think big” and define new ways to evaluate, visualize, and predict talent outcomes and decisions like hiring, promotions, and transfers.

After you have developed peer-reviewed scientific solutions to these unique problems, you will partner with economists, data scientists, software engineers, data engineers, applied scientists, product managers, and UX designers to deliver your solution to tens of thousands of internal customers through world-class product experiences.

About the hiring group
WW Consumer Talent Products Team is looking for a world-class Senior Applied Scientist for our science innovation arm, Skunkworks.

Skunkworks is a cross-functional incubation team within HR, comprising scientists and technologists.

We innovate industry-leading scientific solutions that inform human decision making throughout the talent lifecycle.

We explore complex problems through innovative solutions in Organizational design, Exec development planning, Talent movement, and more! This requires us to invent years ahead of current state.

We are intentional about our innovation by creating experiments to prove our “think big” concepts with pilot customers through prototypes, prior to scaling the solution.

Job responsibilities
Research and implement statistical and ML modeling techniques (e.

g.

Bayesian models, NLP, graph networks, optimization methods)

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