Service Center

CSCS TX

Create, maintain, and optimize ETL processes used to prepare data for Predictive Analytics, reporting and ad-hoc data requests. Support analysts by providing extracted data that can be used to deliver end-to-end solutions to business problems that can be developed rapidly and maintained easily. Develop and evaluate machine learning models using medium/large data-sets and cloud services to drive the growth of all the Caliber Brands.

Role and Responsibilities

• Be inquisitive and have a curiosity about Calibers various business through Predictive Analytic lens. 
• Be a forward-facing business intelligence partner specializing in predictive analytics. 
• Data Transformation and Integration: Extract Structured & Unstructured data from internal databases and external data sources.
• Creates data pipelines and transform data to a structure that is relevant the Machine Learning model(s).  These may be in design phase or for model deployment into production.
• Develop knowledge of current data science and analytics trends.
• While we are a part of the Finance Department, we support projects and change management initiatives across all of Caliber (Operations, Human Resources, Marketing, Compensation, IT, Finance, etc.).
• Deploy Machine learning model results into Power BI reports or internal intranets.
• Understand and use concepts of model validation, Machine Learning data biasing and data leakage.
• Know the difference between Data science, business analytics and data engineering.
• Can effectively communicate ML model interpretability from the results.
• Support the Finance organization in building the roles, skills, processes, and collaboration with other teams necessary to improve Predictive Analytics solutions.
• Help in managing Machine Learning tools, deployment, and data analytics systems while upholding the governance, security, consistency, integrity, and accuracy of all end-user data.

Qualifications and Education Requirements

• Bachelor's degree in Math, Finance, Business Analytics, Engineering or STEM related field, or equivalent work experience, or equivalent combination of education and experience.
• Master's degree/MSBA/MBA/MIS or PhD would be considered a plus.
• 1-2 years of experience in developing business solutions combining Machine Learning, business intelligence, dashboards, and reporting, and/or process improvement & automation with progressive growth in responsibility and scope, using expert knowledge such as data warehouse, data lakes, databases, ETL, reporting tools, data analytics, data modeling.
• Experience with RapidMiner, Alteryx, IBM Watson, SAS Advanced Analytics, Python/R a plus
• Knowledge in data mining, machine learning, artificial intelligence, predictive analytics, and/or big data.
• High standards of Data governance, accuracy, precision, and organization.
• Understanding of Finance and Accounting methodologies, concepts, and principles a plus.
• Understanding of systems and methods to access underlying data and prepare reports.
• Demonstrated ability to turn end-user requirements into actionable tools and insights.
• Experience in data modeling with SSMS, Microsoft Power BI, Power Pivot and/or SSAS Tabular.
• Relevant experience with Microsoft Excel, data modeling and data visualization tools.
• Willingness to work closely with field operations, other teams, and all management levels.
• Articulate with adequate verbal and written communication skills.
• Ability to think creatively, highly driven, and self-motivated.
• Ability to succeed in an entrepreneurial atmosphere and willingness to dig for information.
• Comfortable in a high growth and strong customer service environment.