YourLiebherrCareer: Digital Transformation & AI Analyst

Liebherr•Newport News, VA

2d•Onsite

About The Position

Reporting to the Managing Director – Sales & Service, the Digital Systems & AI Analyst develops and implements data-driven, digital, and AI-enabled solutions across the organization’s equipment divisions and corporate functions. The role applies expertise in data science, software development, systems engineering, automation, and artificial intelligence to support sales, service, market development, customer support, operations, facilities, and strategic business initiatives in collaboration with divisional leaders and cross-functional teams.

Requirements

Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Data Science, Systems Engineering, or a closely related technical discipline.
Up to two years of relevant professional, internship, co-op, or project-based experience.
Practical knowledge of programming, data analytics, databases and SQL, artificial intelligence and machine learning, systems integration, automation, computer and connected systems, and business-intelligence tools.
Applicants must be legally authorized to work in the United States without the need for current or future sponsorship.

Nice To Haves

Experience with Python, SQL, Power BI, APIs, cloud technologies, or AI/LLM platforms is preferred.

Responsibilities

Analyze large and diverse datasets related to equipment sales, service activities, customers, installed equipment population, fleet utilization, market development, product performance, and distribution.
Develop analytical models and tools to identify trends, correlations, market opportunities, operational issues, and potential areas for business improvement.
Collaborate with Finance and Business Analysts to enhance established reporting, dashboards, and KPIs by providing technical analysis, data integration, automation, and engineering-focused insights.
Integrate and analyze information from ERP, CRM, telematics, market databases, financial systems, and other enterprise data sources.
Apply programming, database, statistical, and visualization techniques using tools such as Python, SQL, Power BI, APIs, Excel, and related technologies.
Develop equipment volume forecasts and predictive models using historical volume data, current and anticipated market conditions, and technological evolution affecting equipment demand.
Design, develop, test, and improve AI-based agents and technical applications supporting sales, service, market intelligence, engineering research, and internal information retrieval.
Develop AI-assisted tools capable of collecting, structuring, evaluating, and summarizing information from multiple internal and external data sources.
Evaluate the use of large language models, machine learning, APIs, and emerging AI technologies for practical applications within the organization.
Develop prototypes and proof-of-concept AI applications for sales, service, customer support, market analysis, and management decision-making.
Identify repetitive analytical and information-processing activities and develop automated workflows to improve efficiency, consistency, and data quality.
Evaluate opportunities to connect AI applications with existing enterprise information and data systems.
Test AI-generated results for accuracy, reliability, repeatability, and usefulness in a professional engineering and business environment.
Perform quantitative analysis of equipment markets, customers, competitors, applications, and industry trends across the company's equipment divisions.
Develop automated methods for collecting, structuring, and analyzing market and competitive intelligence.
Develop market-size models, market-share analyses, customer segmentation, equipment-population analyses, and demand forecasts.
Analyze regional and industry-specific trends affecting construction, infrastructure, energy, ports, mining, industrial, and other equipment markets.
Develop data-driven market analyses, forecasts, technical presentations, and strategic recommendations for the Managing Director and divisional management, using Finance-approved data and reporting definitions where applicable.
Develop analytical tools that allow management to identify market opportunities and changes earlier and more systematically.
Analyze technological developments affecting heavy equipment, including automation, electrification, connectivity, telematics, remote diagnostics, digital services, and artificial intelligence.
Analyze equipment-generated and telematics data to identify potential applications in sales, service, fleet management, customer support, and market development.
Evaluate opportunities to combine equipment data with customer, sales, service, and market information.
Support digitalization projects involving connected equipment and data-driven services.
Evaluate emerging technologies and their potential commercial and operational application across the company's equipment divisions.
Analyze existing processes and systems supporting equipment sales, service, distribution, inventory management, customer development, and after-sales support.
Identify opportunities to improve these processes through data integration, automation, artificial intelligence, and digital technologies.
Develop analytical tools supporting customer prioritization, sales opportunity identification, installed-base management, equipment replacement analysis, and service development.
Support the development of digital tools providing management with improved visibility of sales pipelines, service opportunities, customer activity, and market potential.
Work with divisional teams to translate operational requirements into data-driven and technology-based solutions.
Support Marketing through data analytics, automation, and AI-based technologies.
Analyze customer, market, digital-channel, campaign, and event data to evaluate marketing effectiveness and market reach.
Develop analytical approaches for customer segmentation, lead identification, campaign measurement, and market-development activities.
Evaluate AI-based tools for market research, content analysis, customer intelligence, and competitive monitoring.
Develop automated reporting solutions connecting marketing activities with sales and market-development outcomes.
Support selected facility-management and development projects through technical data analysis, modeling, and digital tools.
Analyze operational and facility-related data to support capacity planning, utilization analysis, infrastructure investment, and development decisions.
Develop analytical models and dashboards supporting facility-development projects and capital-investment decisions.
Evaluate opportunities to use sensors, automation, energy data, connected systems, and other digital technologies to improve facility utilization and operational efficiency.
Work directly with the Managing Director on selected strategic, technical, analytical, and digital initiatives across the organization.
Conduct structured quantitative analyses to support strategic business and investment decisions.
Develop analytical models, simulations, reports, and presentations for strategic projects.
Research emerging technologies, markets, competitors, and business models and assess their potential impact on the organization.
Participate in cross-divisional projects requiring the integration of engineering, technology, market, and business information.
Translate complex technical and quantitative information into clear recommendations for executive decision-making.