Requirements
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience,
• Experience in patents or publications at top-tier peer-reviewed conferences or journals,
• Experience programming in Java, C++, Python or related language,
• Experience implementing algorithms using both toolkits and self-developed code,
• (Desirable) PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field,
• (Desirable) Experience with popular deep learning frameworks such as MxNet and Tensor Flow,
• (Desirable) Experience in building machine learning models for business application,
• (Desirable) Experience in causal inferencing and A/B testing,
• (Desirable) Experience with big data libraries and tools, e.g. spark
What the job involves
• 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
