Business Intelligence Analyst

Caliber Collision•Lewisville, TX

1d•Onsite

About The Position

This role is within the Service Center at CSCS TX. The Business Intelligence Analyst will be responsible for creating, maintaining, and optimizing ETL processes to prepare data for Predictive Analytics, reporting, and ad-hoc data requests. They will support analysts by providing extracted data to deliver end-to-end solutions for business problems that can be developed rapidly and maintained easily. The role involves developing and evaluating machine learning models using medium/large datasets and cloud services to drive the growth of all Caliber Brands. While part of the Finance Department, this role supports projects and change management initiatives across all Caliber departments, including Operations, Human Resources, Marketing, Compensation, IT, and Finance. The analyst will deploy machine learning model results into Power BI reports or internal intranets, understand model validation concepts, and communicate ML model interpretability.

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.
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.
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 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.
Must be eligible to work in the U.S. with no restrictions.

Nice To Haves

Master's degree/MSBA/MBA/MIS or PhD would be considered a plus.
Experience with RapidMiner, Alteryx, IBM Watson, SAS Advanced Analytics, Python/R a plus.
Understanding of Finance and Accounting methodologies, concepts, and principles a plus.

Responsibilities

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.
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.
Extract Structured & Unstructured data from internal databases and external data sources.
Create 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.
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.
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.
Turn end-user requirements into actionable tools and insights.
Work closely with field operations, other teams, and all management levels.