Day to Day: 

My client is hiring for a Data Scientist II. You would be joining a team for one of our large retail clients. The team they will join will be compromised of 6-8 team members- an associate manager, lead data scientist, product owner and two other data scientists. They will be working on many new project and specific details will be shared before the interview based on the specific team that the candidate is interviewing with.

Data Scientists on the team will drive customer loyalty, digital conversion, and system efficiencies by delivering innovative data driven solutions. Through these solutions, the data scientists drive material business value, mitigating business and operational risk, and significantly impacts the customer experience. This role works directly with product development, merchandising, marketing, operations, ITS, ecommerce, and vendor partners. The position will lead, consult or oversee multiple highly complex data science projects/programs/domains that have significant impacts and require in-depth technical knowledge across multiple specific architecture disciplines such as technology, solution, business, or information/data.

What You'll Be Doing

• Deliver against the overall data science strategy to drive in-store and digital merchandising, marketing, customer loyalty, and operational performance
• Partner with product development to define requirements which meet system and customer experience needs for data science projects
• Partner with Merchandising, Supply Chain, Operations and customer insights to understand the journey that will be improved with the data science deliverables
• Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs
• Partner with product development and technology teams to deploy pipelines into production MLOps environment following Safe Agile methodology
• You will architect, design, and lead the development and implementation of machine learning algorithms and models for a data science capability within Digital Services, Merchandising, Marketing, Supply Chain and Operations.