Technology. Flexibility. Diversity. At the center of it all are the Digital Accelerator and Advanced Analytics teams at Cummins, working together as a high-energy startup within a Fortune 500 organization. At this Midwestern technology hub, todays sharpest, most curious minds transform what-ifs into realities.
#LifeAtCumminsis aboutPOWERING YOUR POTENTIAL.Youll have global opportunities to develop your career and make your community a better place – to break ground professionally and be your best personally.
About Digital Accelerator and Advanced Analytics:
Cummins’ Digital Accelerator functions as our own tech startup, with strategic access to Fortune 150 resources and talents. Steering the innovation of new experiences for customers, Digital Accelerator is boldly transforming Cummins into a modern and agile technology company. Through the conception, build and launch of inspiring digital solutions, the unique hub of vision and creativity leverages open architecture, connectivity, big data, advanced analytics, internet-of-things, edge computing and more, to drive the company forward on its journey towards smart technologies.
This is an exciting opportunity in Columbus, IN for a Principal Data Scientist. This is an active business facing role where you will work and collaborate with teams to solve problems in a results, customer centric environment.
Your impact will happen in these and other ways:
Manages and Implements advanced analytics projects which solve complex analytical problems using quantitative approaches through a combination of analytical, mathematical and technical skills.
Researches, designs, implements and validates cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes by leveraging complex statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques.
Liaises with business stakeholders and leverages business knowledge to industrialize and monetize insights from advanced analytics projects.
Leads key objectives and business goals through the use of data science methodology.
Leverages data science methodology to solve complex business problems.
Creates algorithms using more complex statistical methodologies through the use of statistical programming languages and tools.
Partners with domain experts to verify model capabilities and translate modeling outputs from statistical inferences into business language.
Partners with Solution Architect to enable appropriate data flow/data model, development using appropriate tools/technology, rapid prototyping and informs the design of analytical products.
Trains and mentors less experienced employees on data science tools and methodologies.
Continuous development and advancement of the organization through knowledge sharing and collaboration.
Participates in planning for advancement of the Data Science profession.