Principal Data Scientist
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, today’s sharpest, most curious minds transform what-ifs into realities.
#LifeAtCummins is about POWERING YOUR POTENTIAL .You’ll have global opportunities to develop your career and make your community a better place - to break ground professionally and be your best personally.
This is an exciting opportunity in Columbus, IN for a Principal Data Scientist
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 more 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 IT resources 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.
Abstract Reasoning - Envisions a solution before implementation by analyzing data, extracting patterns and relationships to establish a problem or solution's feasibility; develops new algorithms and analytical models using process diagrams, flow charts, and textual documentation to explain or conceptualize a complex problem.
Data Mining - Identifies relationships and patterns in data by using a suite of data exploration and data visualization techniques using tools such as PowerBI, R Shiny, SAS JMP, and extracts insights into multivariate data by applying principles of multivariate data mining, small sample statistical inferential tests, dimension reduction techniques to understand the underlying structure of the data and enable sound conclusions upon model building.
Predictive Modeling - Develops statistical and machine learning models using appropriate variable transformations, feature selection strategies, imputation strategies, class rebalancing, resampling strategies and performance metrics to generate descriptive, explanatory or predictive models.
Statistical Foundations - Builds statistical explanatory models for regression, classification, outlier detection, anomaly detection, time series forecasting using knowledge of foundational statistics such as Null Hypotheses Significance Tests, regression models, generalized linear modeling, time series analysis, rank statistics, probability distribution fitting survival analysis, etc. to validate hypotheses or generate predictions for any given statistical or business question.
System Simulation - Creates models of interconnected systems under dynamic operating conditions using mathematical models for physical and mechanical systems (such as Markov chains and Monte Carlo methods) and various simulation packages to reproduce the behavioral characteristics of the system(s) being simulated and to gain insight into how the system(s) reacts under different operating conditions.
Requirements Analysis - Evaluates relationships and interdependencies between requirements based upon their complexity and value to the business in order to determine feasibility and prioritization.
Strategic Roadmap Planning - Produces a high-level, multi-year product and capability roadmap utilizing internal and external business resource, asset and market knowledge and experience to communicate the organization's focus and priorities to internal and external stakeholders.
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.
Balances stakeholders - Anticipating and balancing the needs of multiple stakeholders.
Directs work - Providing direction, delegating, and removing obstacles to get work done.
Drives results - Consistently achieving results, even under tough circumstances.
Education, Licenses, Certifications
College, university, or equivalent degree in statistics, information systems or related field required.
PhD or Master’s degree in Statistics, Econometrics, Computer Science, or equivalent experience preferred.
Compensation and Benefits
Base salary rate commensurate with experience. Additional benefits vary between locations and include options such as our 401(k) Retirement Savings Plan, Cash Balance Pension Plan, Medical/Dental/Life Insurance, Health Savings Account, Domestic Partners Coverage and a full complement of personal and professional benefits.
Cummins and E-verify
At Cummins, we are an equal opportunity and affirmative action employer dedicated to diversity in the workplace. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, gender, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity and/or expression, or other status protected by law. Cummins validates right to work using E-Verify. Cummins will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee’s Form I-9 to confirm work authorization.
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