Sr. Manager - Applied Science, Data Science, Machine Learning
- Seattle, WA
GET READY TO DO SOMETHING BIG!
Over 150 million paid members in 17 countries around the world enjoy the many benefits of Prime, including the best of shopping and entertainment from Amazon. In the U.S. that includes unlimited access to award-winning movies and TV episodes with Prime Video; unlimited access to Prime Music, Prime Reading, Amazon Photos, Twitch Prime; early access to select Lightning Deals, one free pre-released book a month with Amazon First Reads, and more. Prime members can also get deep discounts on select popular products at Whole Foods Market plus an additional 10 percent off hundreds of sale items. Prime was built on the foundation of unlimited fast, free shipping and members receive Prime FREE One-Day Shipping and Prime FREE Same-Day Delivery in more than 8,000 cities and towns, two-hour delivery with Prime Now in more than 30 major cities and unlimited Free Two-Day Shipping on more than 100 million items".
If you want to work on one of Amazon.com's most impactful program and are passionate about writing code that impacts millions of people every day, then the Amazon Prime Team wants to hear from you.
As the Sr. Applied Science Manager to the Prime Machine Learning team you will be in charge of delivering ML Solutions to complex business problems for one of the most beloved customer centric membership programs in the world. As the leader in the space you will manage a core cross functional team of scientists and engineers developing cutting edge recommendation systems and ML engineering pipelines for Prime affecting hundreds of millions of customers internationally. These systems leverage the state of the art in MAB's, Supervised Learning, Reinforcement Learning, and ML technologies at scale (Spark, PySpark, NAWS, Tensorflow, etc.).
You will set the scientific culture (including scientific research, publication, and innovation), strategic vision for ML in the organization (in the short and long term), manage the execution of scientific projects, and influence across other businesses interfacing within Prime. As a shared serviced team, you will support all areas of the Prime business including content optimization, acquisition, and retention (major business pillars within Prime).
The ideal candidate will have a scientific as well as technical expertise, strong business intuition, and a desire to grow and develop others. It also requires excellent written and verbal communication skills to influence business direction (through VP level), frame solutions for non-technical partners, and be an advocate for ML in the org.
• Hire, Grow, and Develop top tier scientific and engineering talent.
• Partner with Sr. Leaders across the organization to frame business problems, establish ML vision, and execute roadmap. Partner with Engineering teams to bring modeling solutions to frontline applications across the business.
• Set the scientific culture and leadership within the Prime Organization, advocating for ML at leadership level
• Be a thought leader on ML engineering, Scientific Research, and Business Strategy, be able to make trade off and executive decisions spanning the end to end ML workflow.
• Be able to translate and communicate out ML driven results
• Identify new opportunities to leverage ML within the organization
• PhD in Quantitative Discipline such as Mathematics, Physics, Computer Science, or Statistics (etc.) or equivalent
• 10+ years of experience in the field applying Machine Learning Solutions to business problems
• 4+ years leading scientists and engineers
• Excellent written, verbal, and interpersonal communication skills
• Ability to think innovatively and creatively, Strong analytic skills and keen business intuition.
• Experience with AWS technologies and code development in one or more computer languages
• Track record of scientific publication and research
• Industry experience building machine learning systems at scale
• Experience with distributed computing including tools such as EMR, Hadoop, Spark
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience building complex and large scale software systems that have been successfully delivered to customers
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
• Exposure to machine learning
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
We believe passionately that employing a diverse workforce is central to our success and we make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, gender, disability, sexual orientation, race, religion or belief.
Back to top