Job
Description
A successful candidate will be comfortable completing tasks under the guidance of leadership, compiling data-driven insights, and contributing to projects (long and short-term) that enhance business functions. They will also gather, analyze and prepare data in various forms for the Corporate Services leadership team, as well as other ad hoc needs and requests. Responsibilities Design and develop visual performance dashboards for Corporate Services and Finance functions to monitor key service delivery metrics. Apply tools such as Tableau, Power BI, and Smartsheet to create effective reporting solutions, ensuring data accuracy and integrity. Complete and implement automation solutions to enhance efficiency and reduce manual effort, bringing to bear tools such as Power Automate, Power Apps, Power Query, Tableau, Smartsheet, and SharePoint. Build and maintain data pipelines, queries, and reports to support strategic decision-making, business operations, and ad hoc analytics requests. Collect, aggregate, and analyze data from multiple systems and data warehouses (e.g., Cvent, Concur, SAP) to provide actionable insights and drive improvements in execution. Support AI automation initiatives, including the maintenance of intake and AI self-service platforms like ServiceNow, while finding opportunities for AI-driven process enhancements. Ensure seamless data integration and system configurations in collaboration with Technology teams, enforcing data governance policies and standardized data connectivity. Proactively identify trends, conduct investigations, and provide data-driven recommendations to functional leaders to improve business performance and operational efficiency. Prepare recurring reports and dashboards, including monthly, quarterly, and annual performance measurements for Corporate Services leadership. Develop and optimize data analytic queries, standardized/custom report layouts, and a library of executive report formats to align reporting processes with business objectives. Apply data science methodologies, including regression, classification, clustering, and predictive modeling, to enhance reporting and analytics capabilities. Conduct in-depth, ad hoc analyses to investigate operational challenges and provide data-driven insights What we expect of you Basic Qualifications: Masters degree and 1 to 3 yearsin Data Analytics, Computer Science, or a related field or & 2 years data analysis, automation or business intelligence experience Bachelors degree and 3 to 5 years in Data Analytics, Computer Science, or a related field or & 4 years data analysis, automation or business intelligence experience Or Associates degree and 7 to 9 years in Data Analytics, Computer Science, or a related field & 5 years data analysis, automation or business intelligence experience Preferred Qualifications: Experience with data analytics, reporting tools, and automation solutions. Strong skills in data visualization and dashboard creation (e.g., Power BI, Tableau). Proficiency in SQL and NoSQL databases, including relational table design, indexing strategies, and writing complex queries, with experience handling big data models, data lakes, and distributed computing frameworks. Ability to work with large datasets and extract meaningful insights. Proficiency in data analytics and visualization tools Expertise in automation platforms and workflows, including Microsoft Power Platform (Power Automate, Power Query, Power Apps, SharePoint, and Pages) to streamline processes and improve efficiency. Experience in programming languages such as Python, R, and JSON for data processing, automation, and analytics. Experience with AI-driven analytics and large language models (LLMs) to enhance data insights and automation capabilities. Experience working with self-service platforms such as ServiceNow to support business functions and automation. Understanding of enterprise data governance principles to ensure data accuracy, integrity, and compliance across reporting and automation systems. Familiarity with additional automation tools, such as UiPath and emerging AI technologies, to drive process optimization. Strong data visualization and storytelling skills, with the ability to translate complex data into meaningful dashboards, executive reports, and infographics. Knowledge of statistical techniques, including regression, clustering, and classification, as well as data discovery and visualization methods such as distributions, histograms, and bar charts. Proven ability to take initiative and complete projects independently, while effectively collaborating across teams and influencing without direct authority. Strong attention to detail and ability to manage multiple tasks effectively. Strong communication skills, with the ability to present insights clearly to leadership and coordinate cross-functional data requests and updates.
