Data Analyst - Field Operations

Ryan Companies United States IncorporatedMinneapolis, MN
537d

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About The Position

Ryan US, Inc. is seeking a Data Analyst to join our team, focusing on supporting the data and analytics needs of our Construction teams, particularly in scheduling and field operations. This role is pivotal in uncovering meaningful connections and insights from various levels of company data, which will ultimately drive smarter business decisions. With nearly 85 years of experience, Ryan is recognized as an industry leader, employing a fully integrated and creative design-build approach to each project. We aim to be a trusted advisor to our clients by delivering creative, accurate, and timely solutions in the dynamic realm of commercial real estate. In this position, you will provide data analytics support for construction operations, emphasizing scheduling and field operations across all regions and product types. You will become a subject matter expert in datasets related to these areas, assisting Field Operations in scrubbing project data upon completion to ensure accurate as-built records for archiving. Your responsibilities will include building, testing, maintaining, and training on dashboards that communicate analysis and trends effectively. You will organize data with a focus on accuracy, speed of access, ease of access, and flexibility, while identifying patterns or trends that support core operational decisions. Additionally, you will influence existing data collection processes by recommending improvements, workflow modifications, systems, or tool enhancements to ensure quality data. Ensuring data quality and accuracy will be a continuous task, involving ongoing data validation, cleansing, and enrichment activities, while also addressing privacy and security components. Collaboration is key in this role, as you will work closely with other data analysts and technology partners, as well as business leaders, to understand their data analysis needs and provide insights and recommendations that inform decision-making.

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