Data Scientist / Business Intel Engineer, EU Prime and Marketing Analytics & Science (PRIMAS)

We are open to hiring this position in any of the following locations: Milan, Madrid, Barcelona.

Are you passionate about giving customers the richest, most inspiring experience in their shopping journey? Do you like to dive deep to understand how customer-centric solutions drive measurable results? Do you enjoy working closely with the business, scientists and software engineers to build scalable products? You are in the right place! Come join our Prime & Marketing Analytics and Science (PRIMAS) team, where your actions will have direct impact to millions of customers!

The EU Marketing & Prime organization is looking for a Business Intelligence Engineer. The PRIMAS team provides a comprehensive understanding of customer segments, affinities and lifetime value. We use the latest data science tools and advanced analytical techniques to study customer purchase and engagement behaviors and generate actionable insights on where, when and how we provide products and programs to our customers to meet their needs and to delight them. We help to increase customer engagement, sales and marketing efficiency. Our systems are built entirely in-house and on automated large-scale analytics systems. You will generate insights, design/deliver/measure experiments and strategies across marketing channels (SEM/SEO, Affiliates, Display, Social, Mobile, Email, Onsite, etc.), engagement products and customer segments. You will improve our understanding of Customer behavior and engagement, design and conduct rigorous experiments on the effectiveness and efficiency of different marketing actions that will inform long term strategy. You will have the opportunity to work on the forefront of consumer analytics tackling some of the most difficult problems in the industry with some of the best scientists, statisticians and software engineers in the field.

Key job responsibilities
You are good at:
• Working on complex loosely defined analytics problems and defining the team's Business Intelligence (BI) strategy. Delivering independently, and influencing the organization's BI architecture
• Providing analytics solutions for complex business problems. Building analyses/solutions that are robust, extensible and scalable. Communicating effectively with management audiences (e.g., narratives, inputs into Business Reviews). Refining Business Intelligence strategies that cross teams and making technical trade-offs for long term/short-term needs.
• Designing and implementing technical solutions with an appropriate analytics strategy and data set design. Understanding system limitations, scaling factors, boundary conditions, and/or the reasons for technical decisions
• Providing analyses, frameworks and solutions that inform multiple teams' business decisions and highlight new opportunities
• Driving best practices in operational excellence, data modelling, and analysis

Basic Qualifications

- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience in the data/BI space
- Experience with forecasting and statistical analysis
- Experience building data pipelines or automated ETL processes
- Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- Experience writing complex SQL queries
- Master's degree, or Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- - Experience with data visualization using Tableau, Quicksight, or similar tools
- - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- - Experience in the data/BI space
- - Experience with forecasting and statistical analysis
- - Experience building data pipelines or automated ETL processes
- - Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
- - Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- - Experience writing complex SQL queries
- - Master's degree, or Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field

Preferred Qualifications

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.

Amazon is an equal opportunities employer