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The Senior Decision Scientist will develop and execute experimental methods to derive actionable insights from data. Responsibilities include collaborating with eCommerce and Digital Marketing leaders, providing strategic recommendations, defining metrics and reports, and leading a stream of testing and experimentation.

As an Azure Data Architect, you will innovate and maintain technology services, develop data strategies using Azure, oversee cloud architecture, integrate AI solutions, collaborate with stakeholders, and provide technical leadership while ensuring compliance and security standards are met.

Leading a small group of DS developers in collaborating and streamlining data science work with product, BA, MLOps. Responsible for DS model development, deployment into multiple markets, code development, model tuning, testing planning, and more. Supporting activities in UAT and development as a contingency resource to ensure timely delivery.

As a Senior Azure Data Engineer, you will develop software and systems for large-scale projects, work across all phases of the SDLC, integrate systems, and maintain technology services to support big data projects for Fortune 500 clients.

The MLOps Engineer will collaborate with Data Scientists and Engineers to deploy machine learning models, streamline model development, and maintain operational tools. Responsibilities include developing scalable ML pipelines, automating model processes, and building knowledge bases for MLOps projects across cloud platforms.

As a Fullstack Engineer, you will develop and maintain backend and frontend for Data to Decision projects, integrate algorithms from backend APIs, and create dynamic infographics. You'll troubleshoot and maintain documentation while collaborating with cross-functional teams for enterprise web applications.

The Lead Data Scientist will drive the delivery of AI/ML solutions in the retail sector. Responsibilities include leading teams, managing data science projects, utilizing algorithms for customer segmentation, forecasting, and optimizing marketing strategies. The role requires collaboration with stakeholders and a strong understanding of end-to-end data science processes.