Amazon’s Global Accounts Receivable team is looking for a Data Scientist to join our fast paced, stimulating environment to help invent the future of Accounts Receivable with technology, and to turn big data into actionable insights.
Our team charter is to optimize credit risks, cash flow, customer satisfaction and internal efficiency. We provide insights and recommendations to senior business leaders in terms of policies, process and systems. We build large-scale models that help our global teams manage their receivables portfolios, run their operations to maximum effect and foresee future trends. We contribute algorithms to O2C systems towards effective credit management.
We are seeking to hire a Data Scientist with strong scientific acumen, technical skills and communication to join our team.
The role will help build global-scale components of our economics and statistical toolkit, initially focusing on trend and regression analysis, machine learning, and more. They will discover and define problems; and find the right quantitative solutions. They will measurably impact the success of the major receivables processes in Amazon's core businesses, including credit and risk management, as well as dunning and collections strategies.
The role will actively interact with business in translating requirements into Data Science problem statements; following through modelling and deployment; and driving continuous improvement and learning. The role will work hand in hand with software engineers, business intelligence engineers and business teams towards implementation at scale.
· Apply judgement to identify and develop science solutions
· Design and develop models to predict process behaviour and outcomes
· Apply advanced statistical and/or machine learning know-how e.g. to optimise predictive abilities
· Develop new data sources to enable statistical modelling and learning; continuously fine-tune data models
· Design and utilise code (Python, R, Scala, etc.) as required
· Formulate experiments to assess AR process strategies
· Collaborate with engineering to build data, algorithms and models
· Communicate scientific solutions and insights effectively to a senior leadership and non-scientific audience
· Bachelor's Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist
· Master’s degree+ in a quantitative field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics.
· 5+ years' of industry experience with data querying languages (e.g. SQL), scripting languages (e.g. Python, R), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.).
· At least 3 years’ experience articulating business questions and using quantitative modelling and statistical analysis techniques to arrive at a solution using available data.
· Experience with Java, C++, R, PL/SQL, Oracle 11g, MS SQL Server and Amazon Web Services: Redshift
· Depth and breadth in quantitative knowledge, quantitative modelling, statistical analysis and problem-solving skills.
· Demonstrable record of accomplishment of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
· Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations.
· Experience with modelling sequential data, statistical forecasting, and time series models.
· Experience processing, filtering, and presenting large quantities (millions to billions of rows) of data.
· PhD in a quantitative field
· Formal training in Statistics, Economics, Econometrics or similar discipline
· Familiarity with business-specific (AR/Accounting) processes
· Depth of knowledge in machine learning algorithms
· Understanding of Amazon Web Services (AWS) technologies
· Experience in supply chain is a plus
· Track record of defining science vision and strategy
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us