Amazon’s global talent is incredibly complex with unique problems to be solved for each line of business. Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s human capital and talent products and processes. GTM Science is a growing interdisciplinary science team within GTM that develops science products and services that facilitate Amazon’s growth and development of talent across all of our businesses and locations around the world.
Our vision in GTM Science is to use machine learning and science to scalably solve organizational challenges focused on talent movement, talent differentiation, employee-role matching, promotion processes, organizational design and succession planning, diversity and inclusion, and new areas that address the evolving needs of our diverse employee base.
We are looking for an experienced machine learning scientist to work on talent science products that draw from a range of fields such as supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning and others on rich and novel datasets. The role has high visibility to senior Amazon business leaders and involves working with other scientists, partnering with dev and product teams to integrate these models into production systems.
As an applied scientist in GTM Science, you will have the opportunity to work on exciting problems in one of the most innovative applications of science in the Human Resources space. You will help to solve high impact business problems in an unconventional domain, and encouraged to patent and publish your contributions. If this kind of work fascinates you, reach out to us to find out more!
· Participate in scoping and planning of GTM’s science products
· Design and execute science-based product ideas and features, project plans and communicate with stakeholders.
· Develop predictive models to understand important business and people-centered outcomes
· Productionize ML and science models at the scale of Amazon
· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· Skilled in Python, R or similar scripting language.
· Basic knowledge of SQL.
· Knowledge and practical experience in more than one of the following areas: machine learning, statistical inference, causal modeling, reinforcement learning, Bayesian methods, predictive analytics, decision theory, recommender systems, deep learning, time series modeling, mixed effects models.
· Demonstrated use of modeling and optimization techniques tailored to meet business needs.
· Excellent technical writing and communication skills and ability to convey scientific concepts to non-technical business audiences.
· Highly adaptable, creative, and thrives in a fast-paced work environment.
· Deep experience in several of the above areas and experience with libraries such as Tensorflow/MxNet/PyTorch.
· Track record of publishing in premier journals and conferences.
· Knowledge of software engineering best practices for the full software development life cycle (i.e., coding standards, code reviews, source control management, build processes, and testing).
· Familiarity with AWS and knowledge of distributed computing.
· Experience with customer or employee sentiment data.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.