Senior Applied Scientist
- Denver, CO
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 Senior Applied Scientist (a.k.a Senior 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.
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 partner closely with product and program owners, as well as scientists and engineers from other disciplines (e.g. economics, statistics, business intelligence, data engineering) with a clear path to business impact. You develop innovative and even frighteningly bold plans and ideas to discover new ways to advance our goals. You will be expected to be a thought leader as we chart new courses with our rapidly growing employee populations, and lead the way in experimenting new ideas that have not yet been explored.
Successful candidates will have a deep knowledge of computing statistical and machine learning methods for large scale prediction problems -or- a deep knowledge of computational optimization methods and mathematical modeling, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems.
• Advise business and program leadership on applicable use of machine learning
• Scope and plan GTM's machine learning science roadmap
• Develop predictive models and optimization for important business and people-centered outcomes
• Design and execute science-based product ideas and features, project plans and communicate with stakeholders
• Productionize ML and science models at the scale of Amazon
• PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
• 3+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language
• MS or PhD in Computer Science, Statistics, Math, Electrical Engineering, Economics or related fields.
• 5+ years of experience applying statistical/ML models in large-scale production applications.
• Skilled in Python, R or similar scripting language.
• Basic knowledge of SQL.
• Extensive 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.
• Track record of innovation and strategic impact across teams
• Executive-facing verbal and written communication and data presentation skills
• Ability to deliver complex analysis/projects when neither problem nor solution is well defined
• Working fluency in SQL, data modeling, data mining
• Proven ability to influence change strategies with data
• 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 an Equal Opportunity Employer - Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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