Responsibilities include: Understanding business requirements and existing challenges and map them to the right scientific solution; Designing effective, scalable, and achievable solutions to key business problems; Developing the right set of metrics to evaluate efficacy of your models and solutions; Prototyping and analyzing new models and business logic; Productionizing your scientific solutions, including writing production-quality critical path code; Communicating, both written and verbally, with both technical and business audiences throughout each project; Publishing findings in internal and/or external conferences and interfacing with the scientific community; Mentoring and developing the scientist community across the organization. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, large language models, mixed integer linear programs (MILPs), reinforcement learning, causal inference, and experiment designs.