Build and develop models that will feed directly into regulatory reporting and consumption component of the water balance
Enrich stakeholder insight of our Big Data Smart Meter set, applying quality assurance techniques and automation processes to deliver consistent reporting
Develop statistical and predictive models that improve understanding of consumption, per capita consumption, business demand and leakage, and feed directly into regulatory reporting
Carry out exploratory analysis, data mining and empirical analysis to identify trends, drivers and opportunities
Apply data science techniques such as linear and multivariate regression, decision trees, Monte Carlo analysis and neural networks to complex business problems
Requirements
Level 5 or higher qualification in Data Science, Computer Science, Statistics, Mathematics or a related quantitative subject, or equivalent professional experience
Lead the development, validation, and ongoing improvement of predictive Customer Lifetime Value (LTV) models while forecasting eCommerce performance and supporting business decisions through advanced analytics.
Locations (2)
Minneapolis, Minnesota, United States
United States
Compensation
Pay Range: $100,000- $135,000. Final compensation will be dependent upon skills & experience.
Responsibilities
Design, build, validate, and maintain predictive LTV models using customer transaction and behavioral data
Develop statistical and machine learning models to forecast eCommerce revenue, orders, conversion rates, and average order value
Perform cohort analysis and customer segmentation to identify trends in purchasing behavior and customer value
Evaluate and continuously improve model accuracy, reliability, and predictive performance
Partner with Marketing, Finance, Product, and Data Engineering teams to apply LTV predictions to customer acquisition, retention, and marketing investment decisions
Requirements
Master's degree in Data Science, Statistics, or a related quantitative field, or equivalent practical experience