Senior Manager, Sciences
- Tempe, AZ
DESCRIPTION
Are you passionate about big data, enjoy solving complex analytical problems, build predictive analytics and descriptive analytics to drive growth at web scale - all in a challenging, fast-paced environment? Amazon's affiliate marketing program, Amazon Associates, spans a large number of websites and blogs worldwide. These sites and bloggers create compelling original content to help customers make informed purchase decisions on Amazon. The Affiliate Marketing Sciences team is responsible for analyzing vast amounts of data on customer transits and purchases influenced by associates, generate insights, build models and develop recommendations to drive growth of the program. We are looking for an experienced and talented leader for our sciences team.
As the leader of the Affiliate Marketing Sciences team, you will partner closely with product, business and technology leaders to identify and prioritize problems, formulate analytical strategy and roadmap to inform decisions to address these problems, hire and grow team members, and deliver on this roadmap. The leader is also responsible for enabling and scaling the impact of data-informed decisions through the development of self-service analytical capabilities so as to accelerate the growth of the Associates Program worldwide.
The ideal candidate will be a proven sciences leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced environment. You will have excellent business, technical, analytical and strategic thinking skills. You are effectively able to work with product, business and technology leaders to define and prioritize key customer problems, build data acquisition and integration pipelines to create data sets, develop statistical and machine learning models and deliver analyses and insights that answer these problems. You will have strong quantitative modeling skills and expertise using data mining and statistical analyses at web-scale to coach and guide the team to produce actionable insights and recommendations. You will lead by example and are comfortable taking on projects and delivering results as an individual contributor.
Responsibilities
• Hire, coach and lead a team of applied and data scientists, and data engineers
• Partner with senior leaders in the Associates Program to develop data-informed business and product strategy, and deliver insights across a wide range of business and technology areas to delight customers and grow the Associates Program worldwide
• Define and lead development of foundational growth enablers, including: self-serve analytics, customer insights, associates acquisition and lifecycle engagement models, segmentation models, experimentation metrics, marketing attribution models, rate optimization models, forecast and lift models, risk models, etc.
• Partner with our Data engineering team to build requirements for data infrastructure necessary to facilitate efficient analysis and reporting
• Lead planning and execution of self-service analytics data infrastructure roadmap using QuickSight and/or Tableau
• Provide guidance and thought-leadership on analytical best practices to team members and business partners
• Translate analytical insights into concrete, actionable recommendations for business or product improvement, and present to senior leadership
• Be a thought leader on data systems, data mining and analysis to scale our capabilities, discover trends and develop insights
• Partner with Product Management team to drive requirements for new products and integrate data during product development
• Discover areas of the customer experience and business that can be automated through machine learning
• Be the voice of analytics, support in-depth business reviews, and present to senior management
BASIC QUALIFICATIONS
• Bachelor's degree in Engineering, Computer science, Math, Statistics, Economics or related field
• 8+ years of experience in business intelligence, big data analytics, statistical methods and machine learning techniques in products or services businesses
• 5+ years of experience leading 5+ people analytical teams
• Excellent customer intuition and demonstrated success in identifying and prioritizing business questions, and using quantitative techniques using available data to deliver solutions to address these questions
• Strong data analysis, problem solving skills, strategic thinking, attention to detail and bias for delivering results
• Expertise in deriving insights from big data analyses to solve business and technical problems
• Strong interpersonal and communication skills, along with ability to explain complex technical concepts and analysis implications clearly across different audiences and varying levels of the organization
PREFERRED QUALIFICATIONS
• Masters or PhD degree in Engineering, Computer Science, Math, Statistics, Economics or related field
• 10+ years of data analytics and machine learning experience in products or services businesses
• Ability to operate in a fast-paced environment and manage multiple competing priorities
• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams
• Ability to think innovatively and creatively about ambiguous technical, product and business problems
• Prior experience leading teams of Applied/Data Scientists, Data Engineers, Software Engineers and Analysts
• Expertise in customer segmentation and customer behavior analysis
• Experience in Machine learning (decision trees, multivariate and logistic regression, kNN, kMeans, deep learning, etc.).
• Experience with data visualization software such as Tableau, QuickSight, and statistical analyses tools such as R, Python, SAS or similar
• Experience writing scripts to manipulate data or automate data pipelines
• Strong record of leading international teams, and working with partners internationally
Amazon.com is an Equal Opportunity-Affirmative Action-Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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