Business Intelligence Analyst - Senior

GPP Database Link Responsible for the preparation of complex and interpretive business analyses and reports. Gathers reporting requirements and analyzes data to provide recurring and ad hoc reports to the organization. Performs quality assurance and tests conclusions to ensure validity of the analysis. Leverages data and analytics to provide or propose solutions that drive operational improvement. Uses globally standardized and/or custom business intelligence dashboards and report formats to support business performance metrics. Delivers recurring reports and/or analyses to internal customers on time. Interprets data accurately and draws accurate conclusions, including what the data mean for the relevant stakeholders. Continually improves the usability of analyses to support decision-making. Plans and manages development of selected projects to enhance business intelligence capabilities: design, budget, communication, and integration with current business intelligence capabilities. Communicates status, risks and expected delivery to manager and/or requester. Develops project plans and implementation plans: roadmaps for the development, testing, deployment, adoption and maintenance of new business intelligence tools or processes. Teaches/coaches or directs the Analyst on the use of business intelligence tools/techniques and how to communicate and present data in a way that is understandable in the business. Builds and sustains Cummins leadership culture by consistently demonstrating all Cummins Leadership Behaviors, not only those included in competencies supporting this role. Competencies:
Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.

Cultivates innovation - Creating new and better ways for the organization to be successful.

Nimble learning - Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.

Optimizes work processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Plans and aligns - Planning and prioritizing work to meet commitments aligned with organizational goals.

Self-development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.

Tech savvy - Anticipating and adopting innovations in business-building digital and technology applications.

Data Analytics - Discovers, interprets and communicates qualitative and quantitative data; determines conclusions relying on knowledge of business or functional frameworks; simultaneously applies statistics, data validity, data visualization, and problem solving approaches to effectively extract meaningful patterns and business insights; presents conclusions and outcomes that enable data driven business decisions.

Data Mining - Extracts insights from data by identifying relationships and patterns through use of a suite of data exploration and data visualization techniques to understand the underlying structure of the data and enable sound conclusions upon model building.

Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.

Project Management - Establishes and maintains the balance of scope, schedule and resources for a temporary effort (a project ). Ensures results/impact from temporary effort are fully realized as possible.

Values differences - Recognizing the value that different perspectives and cultures bring to an organization.

Customer focus - Building strong customer relationships and delivering customer-centric solutions.

Manages complexity - Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.

Machine Learning - Develops and applies analytical models using supervised and unsupervised methods to generate insights used in solving business questions by enabling machines to learn with experience.

Education, Licenses, Certifications:
Demonstrated role competence is required. College, university, or equivalent bachelor s degree in Data sciences, or in Economics, Computer Science, or Statistics / relevant field with a quantitative focus, or experience equivalent is required.
This position may require licensing for compliance with export controls or sanctions regulations.

Experience:
Experience using a variety of business intelligence tools and techniques required. Experience using at least one advanced analytics tool required, e.g., machine language (R), AI, Einstein, etc. Demonstrated ability to correctly analyze data and develop clear and accurate conclusions required. Experience supporting a customer-focused organization is preferred.