Amazon Web Services Data Science Manager - AWS New Initiative in Boston, Massachusetts
AWS is building several new analytics-driven services that will transform the sales and marketing ecosystem. We are looking for a Data Scientist Leader to manage our science team. This leader will work closely with business stakeholders to automate recommendations by creating various tools and machine-learning models to answer complex business questions and provide insights. You will manage a team that provides predictive analytics, recommendations and insights to sales organization, including actionable activities to address existing business questions and opportunities, and collaborate with field sellers, specialized sales, marketing, sales operations. You need to be a sophisticated user of advanced quantitative techniques for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. In addition, the leader must possess excellent interpersonal skills, excellent written communication skills, be able to develop and mentor people, and oversee a portfolio of key business initiatives.
Location: Strong preference for this position to be in Boston, but open to these additional locations: Seattle, WA, Dallas, TX and Arlington, VA. Relocation offered from within the US to any of these locations.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
· Masters in Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent.
· 5+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists.
· Evidence of doing or directing science work with high positive impact on business outcomes.
· Experience hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career track.
· Management experience for working on cross-functional projects.
· Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, that have been successfully integrated in production systems or informed policy decisions.
· Proficient with SQL and at least one scripting language (e.g., R, Python).
· Demonstrable expertise in research design methodologies (e.g., experiments, quasi-experiments, surveys, sampling methods, etc).
· PhD in Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent.
· 8+ years of experience working in data science
· 4+ years of experience managing data scientists skilled with languages such as R, MATLAB, Python or others
· Excellent verbal and written communication skills, ability to convey rigorous mathematical and statistical concepts and considerations to non-experts.
· Experience with AWS technologies like EC2, Redshift, S3, Sagemaker
· Publications or presentation in recognized Machine Learning or Statistical journals/conferences.
· Excellent organizational skills, time management, and program management skills.
· Ability to work on a diverse team or with a diverse range of coworkers
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.
Benefits overview: https://amazon.jobs/en/internal/landing_pages/benefitsoverview-us
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