À propos
Grand Rapids Corp Headquarters - Grand Rapids, MI Position Summary
The Accounting Intern will be responsible for analyzing and adjusting historical financial results to neutralize the impact of weather variability. This role centers on building a data-driven model using heating degree day (HDD) data by month and region to normalize financial performance across multiple years. The position is ideal for a student interested in financial analytics, statistical modeling, and real-world data applications. Key Responsibilities
Analyze multiple years of historical financial data to identify trends and weather-related variability Calculate the impact of heating degree day (HDD) data across months and geographic regions Develop a statistical or data-driven model to quantify the relationship between weather and financial performance (specifically quantities of fuel delivered and delivery labor cost). Adjust historical financial statements to normalize for weather impacts and improve comparability across periods Build a scalable model that can be applied to future periods to normalize financial results for weather impacts Validate data accuracy and ensure consistency across datasets Document methodology, assumptions, and modeling approach Prepare clear reports and visualizations summarizing findings and normalized results Present insights and recommendations to finance leadership Project Focus: Weather Normalization Analysis Align financial data with corresponding HDD data across time periods and regions Quantify sensitivity of financial results to weather fluctuations Remove weather-driven effects to produce normalized financial trends Deliver a final model and summary of key insights to support business decision-making Qualifications
Currently pursuing a Bachelor's degree in Accounting, Data Analytics, Statistics, or a related field Strong analytical and problem-solving skills Proficiency in Microsoft Excel (advanced functions, data modeling, and large dataset handling required) Experience or proficiency in building statistical models or performing data analytics Ability to work with large, multi-source datasets and ensure data integrity Strong attention to detail and organizational skills Effective written and verbal communication skills Preferred Skills (Nice to Have) Experience with regression analysis, time-series analysis, or other statistical techniques Familiarity with tools such as Power BI, Tableau, Python, or R Coursework in statistics, econometrics, or data science What You'll Gain Hands-on experience applying statistical modeling to real-world financial data Exposure to advanced financial analytics and performance normalization techniques Opportunity to build a meaningful, presentation-ready analytical project Direct visibility with finance leadership
Compétences linguistiques
- English
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