Key job responsibilities
This role has 3 main responsibilities: 1) Set the strategic vision for the Applied Science team in collaboration with key stakeholders, and drive the vision forward. This includes up-leveling the team's profile within the broader SVP org and identifying collaboration opportunities with other teams and execute on them, as well as contributing actively to annual planning, product roadmap prioritization, and maintaining a high bar on operational excellence, 2) Create mechanisms for the smooth functioning of your team, including mechanisms for auditing, sprint planning, and execution, 3) Hire & Develop your team, including creating appropriate scope of work for your team members to set them up for success.
Your team will partner closely with Product Managers, Software Development Managers, and Software/ML engineers to envision, and bring to life features and experiences that delight Amazon shoppers WW. In addition, this team also invests in developing strong thought leadership with cross-organization influence, as well as publishing papers at prestigious internal and external AI / ML conferences.
As the Applied Science Manager, you will be responsible for guiding your team in the creation and deployment of sophisticated algorithms and models that drive measurable improvements in customer satisfaction and business metrics. You will identify high-impact opportunities and translate complex business problems into actionable data science solutions.
BASIC QUALIFICATIONS
- 5+ years of scientists or machine learning engineers management experience
- 6+ years of building machine learning models or developing algorithms for business application experience
PREFERRED QUALIFICATIONS
- Experience building machine learning models or developing algorithms for business application
- Experience with the Scrum methodology (or similar alternatives) for agile software development
- Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Strong publication record at top ML conferences and journals
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.