Are you interested in creating a large business impact on millions of customers through the use of machine learning?

We are seeking an Applied Scientist to join our PriMA (Prime & Marketing) science team to work on developing state-of-the-art solutions to model customer behavior, improve the engagement of our existing customers, and help us grow our customer base.

In this role, you will collaborate with cross-functional teams and stakeholders to solve problems, and you will regularly interact with software engineering teams and business leadership.

Some of the scientific and technical challenges you will tackle in this role are:

• Modeling customer dynamics and how customer behavior changes over time.
• Building recommender systems that can nudge customers and engage them with our products and offers.
• Measuring marketing campaigns across external marketing channels (Youtube, TikTok, Google,....)
• Modeling the causal impact that some actions have over customers.

• Develop accurate and scalable machine learning models to address business use cases ranging from: modeling customer behavior, causal inferencing to model the value of customer incentivizes, recommender systems to increase customer engagement, or modeling and measurement marketing channels.
• Lead and partner with engineering teams to drive modeling and technical design for complex business problems, often guiding engineers to apply the best scientific practices in software development.
• Lead complex modeling analyses to help management and business stakeholders making key business decisions.

About the team
The PriMA (Prime & Marketing) science team is the science team that support the science needs of the EU Prime and Marketing organization, an org that supports the Prime and Marketing programs in European marketplaces and comprises 250-300 employees.

The science team (our team), is part of a larger tech tech team of 50 people (comprising other job families like SDEs or BIEs) that gives support to all the tech needs of the Prime & marketing org.

We are open to hiring candidates to work out of one of the following locations:
Amsterdam, NLD

Basic qualifications

• PhD, or a Master's degree and experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience building machine learning models or developing algorithms for business application
• Experience programming in Java, C++, Python or related language
• Have publications at top-tier peer-reviewed conferences or journals
• Experience implementing algorithms using both toolkits and self-developed code
• Experience with popular deep learning frameworks such as MxNet and Tensor Flow
  

Preferred Qualifications

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience in professional software development
• Experience in causal inferencing and A/B testing.
• Experience with big data libraries and tools, e.g. spark.