Kansas City Southern Railway Fuel Conservation Data Scientist in Kansas City, Missouri
Fuel Conservation Data Scientist
KCS is looking for highly motivated Data Scientist who is passionate about demonstrating their ability to make decisions through quantitative analytics and empirical evidence to improve Fuel Efficiency. This position on our Fuel Conservation team will be utilizing Big Data platform architecture, data-driven quantitative analytics, and railroad operations-related mathematical modeling to enable data driven decisions by the business. Responsible for developing and implementing KCS' mathematical model assets and development capabilities to extract and analyze fuel consumption data in the United States & Mexico, driving insights and real-time results for our Operations team that impact their most strategic business decisions. Work to navigate structured and unstructured data, from engineering its extraction to performing statistical analysis to deriving valuable mathematical predictive model assets. Lead financial modeling/statistical analysis, data mining & synthesis, and leading indicator/scorecard reporting efforts to ensure accurate and timely results and information is available regarding fuel consumption and progress against improvement targets.
Performs detailed statistical and financial analysis in support of fuel opportunity identification and solution support. Discover explanatory variables in high-dimensionality collections of data that relate to financially, and/or operationally important use-cases.
Cultivates data mining capabilities to utilize fuel burn trends & correlations with business metrics. Design and develop analysis systems to extract meaning from large scale structured and unstructured fuel consumption and railroad operations data.
Helps business owners uncover hidden opportunities using data and analytics including machine learning and make recommendations for new metrics, techniques, and strategies to improve the business.
Implements prototypes of actionable decision support systems using rapid methods
Monitors monthly fuel usage and data to predict future fuel usage from key operational inputs - manage and produce fuel reports & score cards for KCSR and KCSM.
Works with multiple cross functional departments to progress various fuel conservation initiatives (i.e., Mechanical, Supply, Environmental, Operating Practices, etc.)
Exemplifies KCS Vision, Values, and Culture in each and every interaction with team, clients, and stakeholders.
Bachelor’s degree from an accredited institution in Data Science, Computer Science or Statistics is required.
Five years of experience using R, Python, or equivalent.
Five years of experience using SQL.
Five years of fuel conservation experience, preferably within the transportation industry.
Master’s degree in Data Science, Computer Science or Statistics
Five years working with Big Data, preferably within the transportation industry, including:
Working with large multivariate data sets, the application of advanced analytics and data mining, and the development and implementation of mathematical models, and
Interacting with (querying, cleaning, transforming, analyzing and presenting) data in a business environment.
Expert in R or Python for use in data analysis
Intermediate knowledge and experience of relational databases and SQL
Strong programming skill in multiple languages, comfortable learning new ones quickly
Experience in translating output from statistical models to business value through creative data visualization techniques.
Proficiency in English and Spanish preferred
The duties listed are representative of the job; however, it in no way states or implies that these are the only duties a person may be required to perform. The omission of specific statements of duties does not exclude them from the position if the work is similar, related or is an essential function of the position.
We are proud to be an EEO/AA employer/Veteran/Disabled. We maintain a drug-free workplace and perform pre-employment substance abuse testing.
Kansas City, Missouri, United States