Sr. Manager, Applied Science, Marketing Measurement and Performance Science (MAPS)

Amazon • Seattle, WA

10d

About The Position

Amazon’s Customer Behavior Analytics org is looking for an Senior Manager, Applied Science, to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations.

A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate complex business problems into scientific challenge, and deliver data driven solutions - which will allow Amazon to make key investment decisions.You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale. You should have strong analytical and communication skills, be able to work with stakeholders and partners which include world-wide business leaders, distinguished scientist, economist, product managers and software teams. You will apply your expertise in Economics, ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.

Requirements

• 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
• Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• Experience building large-scale machine learning and AI solutions at Internet scale
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Nice To Haves

• 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
• 5+ years of hands-on work in big data, machine learning and predictive modeling experience
• 5+ years of people management experience
• PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• Experience in practical work applying ML to solve complex problems for large scale applications
• Experience working with big data, machine learning and predictive modeling
• Experience in people management
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
• Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language
• Experience researching actual applications

Responsibilities

• Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions
• Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions
• Recruit high performing Economist, Applied Scientists and BIEs to the team and provide mentorship.
• Establish team mechanisms, including team building, planning, and document reviews.
• Review and audit modeling processes and results from scientists within and outside your team
• Work with marketing leadership to align our measurement plan with business strategy
• Formalize assumptions about how our models are expected to behave and explain why they are reasonable
• Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level