Data Analytics Manager

Job description

DESCRIPTION

At Amazon, we're always working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a dynamic, organized, and customer-focused data analytics leader who is interested in guiding key business decisions for one of Amazon's emerging self-contained business verticals, Amazon Pay. At Amazon Pay, we are inventing the next frontier of connected commerce. We enable merchants to leverage our trusted, seamless buying experience to allow more than 300 million active Amazon customers to purchase from them—online, in-store, by voice, and across an expanding array of consumer devices.

As the leader of the Analytics & Data Science team, you will have broad latitude to interpret data and influence the organization's senior management. You should be passionate about working with huge datasets and should be someone who loves to bring data together to answer complex business questions that deepen our understanding of our customers: buyers and merchants. You and your team of data engineers, business analysts, and data scientists will build and streamline data infrastructure, define methodologies, and create self-service business reporting and insight tools. Over time, you will lead the development of statistical and machine learning models and work closely with our engineering team to implement solutions designed to improve the success of the Amazon Pay business and delight our customers. You will contribute to the company's intellectual property and will be accountable for the quality, accuracy, and adoption of the analytical solutions your team develops.

This role requires an individual with excellent team leadership skills, outstanding business acumen, and the ability to work across product management, marketing, engineering, finance, and sales teams, as well as country specific business leads to drive business outcomes. We are looking for a leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.

Key Responsibilities include:
· Leading data engineers to build a solid data infrastructure
· Leading and developing a team of business analysts.
· Building applied scientist and machine learning capabilities and models to solve business and customer problems.
· Working with functional business leaders to build scalable processes and metrics.
· Developing a long term analytical strategy and self-service reporting capabilities and drive the implementation of that strategy.
· Using analytics to influence multiple departments, increasing their productivity and effectiveness to achieve strategic goals.
· Creating and deliver reporting, critical for tracking and managing the business, including weekly, monthly, and quarterly operational metric reports.

Desired profile

BASIC QUALIFICATIONS

· Bachelor's degree in math, computer science, engineering, finance, statistics, or a related technical field.
· Proven analytics thought leader with experience leading and growing world class analytics and data science teams
· 10+ years of professional experience and passion for working with large data sets plus deep experience in statistical analysis, advanced modeling techniques, data mining and business analysis. 3+ years managing teams of 4 contributors or more.
· Ability to attack complex business questions with data; the curiosity to dive deep, identify the root cause rather than just spot the trends.
· Ability to thrive in an environment that is tasked with providing data-driven decision support and business intelligence that is timely, accurate and actionable.
· Ability to effectively prioritize projects, manage multiple competing priorities simultaneously, and drive projects to completion under tight deadlines
· Experience in data mining using databases in a business environment with large-scale, complex datasets.
· Proven track record of strong verbal/written communication & data presentation skills, including an ability to effectively communicate with both business and technical teams across the world.