Senior Data Scientist, Global Finance Operations

Job description

DESCRIPTION

Amazon’s Global Accounts Receivable 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 charter of the nascent Data Science team is to optimise 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 Senior Data Scientist with strong leadership and communication skills to join our team.

The role will help us build our O2C and credit risk management toolkit. They will discover and define problems; will analyze vast amounts of business data; develop insights for decision making at the leadership and the daily process level; and build algorithms for running our core O2C processes, including collections strategies, credit management and more. The successful role holder will have a measurable impact of Amazon's global cash flow.

As a thought leader, the role will guide software engineers, business intelligence engineers and business teams, towards building accurate predictive models and algorithms, and deploying automated software solutions at scale.

The role will play an active role in translating business and functional requirements into concrete deliverables; following through deployment; and driving continuous improvement and learning.

We are building a new team and this is an opportunity for you to define the foundations for this space.

This role is based in Amazon's HQ2 in Arlington, VA.

Selected Responsibilities
· Apply judgement to identify opportunities and develop science solutions
· Design and develop models to predict payment behaviour
· Run observational studies addressing collections strategies across our global geographies and business channels
· Identify account clusters across business channels, at a global scale
· Formulate experiments to assess AR process strategies
· Optimise the activities of our transactional 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
· Collaborate with engineering to build data, algorithms and models
· Communicate scientific solutions and insights effectively to a senior leadership and non-scientific audience

PREFERRED QUALIFICATIONS

· 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.

Desired profile

BASIC QUALIFICATIONS

· Bachelor's Degree
· 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 4+ years working as a Data Scientist
· 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.