Amazon’s global Finance Operations team is looking for an experienced Senior 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.
The mission of Global Accounts Receivable is to foster positive interaction with our customers and optimise Free Cash Flow by improving the scale, speed, accuracy and productivity of the order-to-cash (O2C) cycle. We design O2C processes and systems so as to simplify business interaction between our customers and Amazon in all channels we support.
The charter of the nascent Data Science area is to maximize Amazon’s return on our receivables investment in terms of Free Cash Flow, and customer satisfaction. We accomplish this by applying advanced statistical methods and empirical analysis to predict and evaluate customer behaviour. We provide data-driven recommendations to senior business leaders to optimize the O2C cycle in terms of policies, process and systems.
We are seeking to hire a Senior Data Scientist with strong leadership and communication skills to join our team.
Once in the role, you will help us build the future roadmap of Data Science at Global Accounts Receivable. You will discover and define problems; your quantitative solutions will impact the core business of Amazon. You will analyze large amounts of business data and develop metrics, insights and predictions for decision making at the leadership and the daily process level.
Whether predictive customer behaviour analysis, forecasting of payment risk and mitigation across our sales channels and geographies, the design of learning processes, Global Accounts Receivable offers a plethora of quantitative areas with cash flow generation opportunities at a global scale.
You will act as a thought leader of a team of software engineers, business intelligence engineers and business teams, to build accurate predictive models and algorithms, and deploy automated software solutions to make data more actionable to manage our business at scale.
You will play an active role in translating business and functional requirements into concrete deliverables and working closely with software development teams to put solutions into Production.
We are building a new team and this is an opportunity for you to define the scientific vision for this space.
This role is based in Amazon's HQ2 in Arlington, VA.
· Apply business judgement to identify opportunities and develop science strategies
· Design and develop predictive systems pertaining to customers’ payment behaviour
· Run observational studies addressing dunning strategies across our global geographies and business channels
· Apply advanced statistical analysis in a multi-variate, sequential process environment in order to identify cash flow drivers
· Apply statistical and/or machine learning know-how e.g. to optimise the collections activities of our workforce
· 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
· Master’s degree or higher in a quantitative field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics.
· 7+ 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. Excellent quantitative modelling, statistical analysis skills 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 or Economics
· 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.