Data Scientist- Amazon Business Payments

Looking for a career at a company that seeks to be Earth’s most customer-centric company? Are you passionate about leveraging data to build ML based production systems? Does the prospect of applying science to impactful business problems excite you? Do you like getting "scrappy" with data and science tools to answer challenging product and customer behavior questions? Do you enjoy building flexible, performant, and global solutions for complex financial and risk problems? If so, here is a great opportunity to consider!

Amazon Business to Business Payments (B2B) is seeking a Data Scientist who combines their scientific and technical expertise with business intuition to build flexible, performant, and global solutions for complex financial and risk problems. You will develop and deploy production models to enhance our product features & processes that will delight our customers.


As a Data Scientist in the Credit Systems Research team, you will design and build systems that support financial products. You will work closely with business partners, software and data engineers to build and deploy scalable solutions that deliver exceptional value for our customers. You will utilize intellectual and technical capabilities, problem solving and analytical skills, and excellent communication to deliver customer value. You will partner with product and operations management to launch new, or improve existing, financial products within Amazon.

Responsibilities
You will help create our science tools and data assets, then use necessary technical & scientific methods and conduct analyses to derive insights that are critical to business success. You will be responsible for researching as well as educating the business, product, marketing, and business/product development teams on the implementation of the models and data-driven insights to enable day-to-day and strategic decision making. You will partner with our marketing, product management, global engineering, operations and Finance teams to:
· Contribute to the development and enhancement of business payment/lending products and features.
· Use data mining, machine learning, model building, and other analytical/scientific techniques to develop and maintain customer segmentation and predictive models to drive the business and improve our machine learning engine.
· Make recommendations for new metrics, techniques, and strategies to improve campaign targeting and measurement.
· Improve targeting capabilities and uncover hidden opportunities using data, analytics and machine learning.
· Understand business and product strategies, goals and objectives. Set the research roadmap to drive the goals of the business.
· Own or co-own the analytics for one or more product areas, lead planning, execution and delivery of projects.
· Analyze and solve problems at their root, stepping back to understand the broader context.
· Interface with all internal related and ancillary teams to deliver data and analytics as requested.
· Support the maintenance and performance of end-to-end model development, implementation, deployment, and use process.
· Provide support on experimental design, exploratory data analysis, and data management.

Basic Qualifications

· Bachelor’s degree in a quantitative area such as math, statistics, computer science, economics, engineering or equivalent experience
· Advanced degree in a quantitative field or equivalent professional experience in a business environment or advanced degree in a quantitative field. Experience in deploying production systems and working with software engineers
· Experience with A/B testing, statistics and model development.
· Proficient in using SQL, ETL, Data Warehouse solutions and databases in a business environment with large-scale, complex datasets
· Ability to process large data sets from multiple data sources
· Ability to solve complex business problems.

Preferred Qualifications

· Graduate degree in Math, Statistics, Economics, Finance, Computer Science, Engineering, Statistics or other related fields from an accredited university.
· Experience in payments, business analysis, lending, ML and model development and deployment, product management, credit, market, or fraud risk areas
· Experience in complex data cleansing, data validation and data management.
· Experience translating analysis results into business recommendations.
· Experience in using Python, R, SAS, SPSS, Matlab or other Statistical / Machine Learning Software.
· Advanced skills in data visualization tools like Quicksight, Tableau or similar BI tools.
· Hands on experience with statistical analysis and predictive modeling.
· Effective written and verbal communication skills.
Amazon is an equal opportunity employer.