Applied Scientist

Job description

DESCRIPTION

“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.”

Please visit https://www.amazon.science for more information

Amazon's Payment Products team manages Amazon branded payment offerings globally. These products are growing rapidly and we are continuously adding new market-leading features and launching new products. Our payments products (Amazon Co-Branded Credit Cards, Private Labeled Credit Cards, Non-Amazon Branded Credit Cards, Shop with Points and cross-currency converter) provide the most innovative payment experience on and off Amazon. Our team of high caliber software developers, statisticians, analysts and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between click through rate, approval rates and lifetime value. We leverage the wealth of Amazon’s information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon’s technological infrastructure to display the right offerings in real time. We work closely with product managers to understand their business, collect requirements and deliver high value analytics and insights for the Payments team that drive acquisition, usage and loyalty. Our petabytes of data have the ability to improve the shopping experience for hundreds of millions of consumers worldwide. Our goal is to delight our customers with their purchasing experience. Those of us who love to work with data see this as the pinnacle of opportunities that you cannot find anywhere else in the world.

We are seeking an exceptionally talented individual to improve our analytic capabilities. This is an opportunity to join a group with a broad charter and stakeholders across Amazon. In this role, you will be working in one of the world's largest and most complex data warehouse environments. You should be passionate about working with huge datasets and be someone who loves to bring data together to answer business questions. You should have deep expertise in creation and management of datasets and the proven ability to translate the data into meaningful insights. You will have to work with a group of applied and data scientists and play an integral role in strategic decision-making.

The right candidate will possess excellent business and communication skills, work with business owners to develop and define key business questions, and prioritize the work across your team in order to support the broader business initiatives. You should have a solid understanding of efficient and scalable data mining and an ability to use the data in financial and statistical modeling.

PREFERRED QUALIFICATIONS

· PhD in Mathematics, Computer Science, Statistics, Machine Learning, or a related quantitative field
· 5+ years of relevant work experience
· Significant peer reviewed scientific contributions in relevant field.
· Experience applying theoretical models in an applied environment.
· Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Non-Parametrics methods
· Expert in more than one more major programming languages (Java, C++ or similar) and at least one scripting language (Python, Perl, or similar)
· Strong fundamentals in data structures, problem solving, algorithm design and complexity analysis
· Experience with defining organizational research and development practices in an industry setting. Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
· Ability to work effectively within an interdisciplinary team of Data Engineers, BIEs, and Product Managers.
· Experience in online advertising, loyalty programs or financial services (payments products, specifically credit cards would be ideal).

Desired profile

BASIC QUALIFICATIONS

· MS in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 3+ years of hands-on experience in predictive modeling and analysis
· 2+ years hands-on experience programming in Python, R, Java, C#, C++ or other similar programming languages
· Proficiency in model development, model validation and model implementation for large-scale applications
· Ability to convey mathematical results to non-science stakeholders
· Strong communication and data presentation skills