Financial Analytics Intern

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