· MS in a quantitative field such as Computer Science, Mathematics, Statistics or related field
· Multiple years of relevant work experience in BI, Analytics, or Data Science or comparable fields
· Proven SQL and Python (or similar) skills in transformation, optimization and analysis of massive structured and unstructured data sets
· Track record of developing and applying statistical/ML models to business problems
· Excellent written and verbal communication skills including data visualization, especially in regards to quantitative topics discussed with non-technical colleagues
· Ability to influence multiple stakeholders to align roadmap, priorities and drive change
· Strong organizational and multitasking skills with ability to balance competing priorities
We are looking for candidates that are passionate about big data and statistical modelling/machine learning (ML). In this role you will analyze customer behavior data and work closely with a team of product managers to make business recommendations and drive enhancements of our customer experience. Beyond this you will lead strategic deep dives and build algorithmic solutions that allow us to delight Amazon customers at every turn.
The ideal candidate has a strong track record and end-to-end ownership of the full stack of data analysis (data engineering, ETL, data modelling/mining, and statistical/ML analysis), with a high fluency in SQL and Python, R or similar scripting and modelling software. You should also thrive on independence and be relentless in finding automated solutions and eliminating manual solutions.
· Help to develop and deliver against an analytics roadmap by working with business leaders on strategically prioritizing numerous requests and long-term adoption of new technologies
· Use statistical and ML techniques to generate insights from big data and derive actions, as well as communicating results in front of senior leadership
· Deep dive into relevant insights to derive the overall strategy, targets and specific actions to increase the engagement of our customers
· Work closely with both tech and non-tech stakeholders