The Helper Bees is seeking to develop and maintain sophisticated forecasting models to drive critical business decisions, including predicting key business metrics such as phone call volumes, unit sales, new customer acquisition, and other operational KPIs.
Requirements
- Advanced proficiency in Python (pandas, scikit-learn, statsmodels, matplotlib) or R (forecast, tidyverse, ggplot2)
- Deep understanding of time series analysis, regression modeling, and statistical forecasting techniques
- Experience with ensemble methods, neural networks, and advanced ML algorithms for forecasting
- Strong SQL skills for data extraction and manipulation
- Proficiency in Tableau, Power BI, or equivalent visualization tools
- Experience with Git and collaborative development practices
- Programming skills in Python or R
Responsibilities
- Design, build, and deploy forecasting models for multiple business metrics (call volumes, sales units, revenue, customer acquisition)
- Implement time series analysis using statistical methods (ARIMA, exponential smoothing, seasonal decomposition) and machine learning approaches
- Develop ensemble models that combine multiple forecasting techniques for optimal accuracy
- Perform feature engineering incorporating external factors such as marketing spend, seasonality, economic indicators, and promotional activities
- Continuously monitor model performance and implement improvements to maintain forecast accuracy
- Extract, clean, and prepare large datasets from multiple sources for forecasting analysis
- Conduct exploratory data analysis to identify trends, patterns, and anomalies in historical data
Other
- Bachelor's degree in Statistics, Data Science, Economics, Operations Research, or related quantitative field
- 4+ years of hands-on experience in business forecasting, demand planning, or predictive analytics
- Ability to work independently and manage multiple forecasting projects simultaneously
- Excellent written and verbal communication skills
- Ability to remain at your designated workstation for the duration of the workday
