Worthington Industries (NYSE: WOR) is a global company that processes steel for use in the automotive, construction, hardware, aerospace and many other industries. Our family of 10,000 employees in 82 facilities throughout 11 countries has helped us earn the respect of our customers, our communities and our industry. With systems developed to conform to international standards for quality, environmental management and occupational health and safety, we consistently rank at the top of the Jacobson & Associates Survey, which ranks customer satisfaction among major steel suppliers.
With sales of approximately $2.5 billion annually, our company is North America's premier value-added steel processor and a leader in manufactured pressure cylinders, such as propane, oxygen and helium tanks, hand torches, refrigerant and industrial cylinders, camping cylinders, compressed natural gas storage cylinders and scuba tanks; framing systems and stairs for mid-rise buildings; steel pallets and racks.
Since 1955, Worthington Industries and its employees have lived a customer-centered philosophy, based on the Golden Rule. We often describe our company as "stability in motion," meaning our customers can trust us for old-fashioned quality, reliability and superior service, but also can look to us for dynamic innovation.
This position is seeking someone with highly developed Advanced Analytics & Predictive Modeling skills to work on a great variety of quantitative business opportunities, including, but not limited to Demand Analytics, Pricing Analytics, Safety Analytics and Inventory Optimization.
This uniquely influential role will support the business using analytics in shaping companywide decisions. You will collaborate with business partners using rigorous quantitative analysis and modeling techniques to support fact-based decision making.
The position is also responsible for continual communication and education of the business on ongoing and potential analytic opportunities. An ideal candidate will not be shy to challenge the status quo, with creative, unbiased and purposeful insights from data.
-Timely delivering knowledge nuggets and scored datasets using intuitive reports & dashboards to maintain a high level of stakeholder satisfaction.
-Understand the business to identify the next big business opportunity to address using Advanced Business Analytics.
-Support evangelism of Business Analytics and continual advancement of organization’s analytic culture/quotient. Be a change agent!
-Ability to understand and stay in front of emerging trends in applied Advanced Analytics, Predictive Modeling & Data Science and utilizes this knowledge to solve business issues ingeniously enabling fact-based decision making.
-Possess a strong statistical programming ability.
-Ability to execute multiple and complex projects concurrently using the CRISP-DM process.
-Excellent communication and interpersonal skills are required along with demonstrated experience working with cross-functional teams.
-Builds custom quantitative models by applying advanced statistical methods to drive Descriptive, Predictive & Prescriptive Analytics through causal and predictive modeling, forecasting, data mining, simulation, and/or optimization
-Demonstrates ability to clearly and concisely communicate complex information and results to a variety of audiences.
-Must exhibit a strong aptitude and drive to continually learn about all functional areas to implement/automate/operationalize models to day-to-day decision making.
-Master’s degree in a quantitative discipline with a Business Background (Advanced/Predictive Analytics, Management Science, Statistics, Economics or related quantitative discipline)
-Expertise in PL/SQL, SQL and ETL from data-warehouse and external data
-Minimum of 1-2 years Advanced Analytics/Predictive Modeling experience with statistical software, e.g.: IBM SPSS Modeler, SAS Enterprise Guide/Miner, SAS BASE, R.
-Expertise with segmentation modeling & profiling, principal component analysis, boosting & bagging, decision trees, neural networks, regression, cox-regression, time-series models, oversampling, cross validation, Ensemble modeling, Conjoint Analysis, and profitability models.
-Advanced expertise in Excel (Macros, Pivot Tables), Power Point (presentations) are required.
-Advanced knowledge of industry data sources and ability to work with large databases and datasets for extraction, conversion into useful business information, and analytical purposes
-The business acumen to translate raw data to fully functional prescriptive analytics tools enabling evidence based Decision Support/Management.