Services Data Analytics Analyst

Vertiv•Westerville, OH

About The Position

The Services Data Analytics Analyst will join the Business Analytics team to design, develop, test, and support data analytics and business intelligence solutions that drive insights and decision-making across multiple business functions. The role focuses on transforming raw data into strategic business value by working with large datasets and building scalable analytics and BI solutions. The position involves collecting and integrating data from legacy systems, Oracle EBS, cloud platforms, and AI-powered sources; developing AI-enabled pipelines for structured and unstructured data; and creating reports, visualizations, and dashboards for departments including Sales, Finance, Operations, Marketing, Procurement, and Supply Chain. The analyst applies statistical and machine learning methods to identify trends, anomalies, customer behavior, and business performance, and uses AI models to simulate scenarios and support business decisions. The analyst builds, deploys, maintains, and improves BI and AI/ML-enabled dashboards and tools using Microsoft SQL Server, Power BI, and the Microsoft BI stack. The role also supports AI-enhanced workflows, recommendation engines, enterprise integrations, and documentation of models, pipelines, and governance practices. The position requires cross-functional collaboration, support for leadership decision-making, ongoing evaluation of BI platforms and emerging technologies, and the ability to work flexibly in an interrupt-driven environment. Travel may be required domestically and internationally.

Requirements

Bachelor’s degree in Information Technology or a related field.
1–3 years of business domain experience working with large datasets and solving complex business problems.
Strong command of SQL and relational databases.
Experience with Microsoft SQL Server, Power BI, and the Microsoft BI stack.
Programming skills in .NET, Python, C#, or JavaScript.
Familiarity with SDLC methodologies.
Familiarity with AI/ML frameworks and experience applying machine learning models to real-world business problems.
Exceptional analytical and problem-solving skills.
Strong communication and presentation abilities.
High attention to detail and time management.
Ability to work independently and manage multiple priorities.
Strong customer focus and interpersonal effectiveness.
Comfort working in a matrixed organization and engaging with all organizational levels.
Strategic thinking and a results-oriented approach.
Ability to mentor, train, and foster cross-team collaboration.
Willingness to work flexible hours.
Ability to maintain overall productivity in an interrupt-driven environment.
Willingness to travel as required, domestically and internationally.

Nice To Haves

Experience with Oracle EBS.
Experience with SharePoint.

Responsibilities

Collaborate with the Business Analytics team to build and maintain scalable analytics and BI solutions.
Work with large datasets to uncover actionable insights that support business strategies.
Collect and integrate data from legacy systems, Oracle EBS, cloud platforms, and emerging AI-powered data sources.
Design and develop scalable, AI-enabled analytics pipelines for structured and unstructured data.
Identify valuable data sources and automate data collection, transformation, and enrichment.
Create reports, visualizations, and dashboards using AI-driven insights for Sales, Finance, Operations, Marketing, Procurement, and Supply Chain.
Apply machine learning techniques and statistical models to uncover trends, detect anomalies, and predict outcomes.
Analyze customer behavior and business performance, and use AI models to simulate scenarios and optimize business decisions.
Build, deploy, and maintain BI and AI/ML-enabled dashboards and analytics tools using Microsoft SQL Server, Power BI, and the Microsoft BI stack.
Develop AI-enhanced workflow solutions and recommendation engines that support business processes.
Ensure the performance, scalability, and security of data products, incorporating AI components when appropriate.
Support integration of AI services with enterprise applications and data ecosystems.
Develop and maintain technical documentation for AI models, data pipelines, and governance practices.
Monitor and improve existing BI and AI systems for accuracy, relevance, and usability.
Explore and evaluate AI technologies and frameworks for intelligent analytics solutions.
Support leadership with data-driven insights for strategic decision-making.
Continuously evaluate and enhance BI platforms, stay current with BI and analytics trends, and recommend improvements.
Participate in cross-functional collaboration and technical integrations.
Maintain productivity in an interrupt-driven environment and travel as required, domestically and internationally.