The business problem is to optimize revenue and reduce revenue churn by using data analysis and predictive modeling.
Requirements
- Experience with statistical analysis and modeling techniques
- Familiarity with machine learning libraries and frameworks such as scikit-learn, TensorFlow, or PyTorch
- Knowledge of database systems and SQL
- Experience working with disparate data sets from multiple sources
- Familiarity with cloud computing platforms such as AWS, Azure, or GCP
- Understanding of software development best practices, including version control and code review
Responsibilities
- Collaborate with sales, support, analytics, and development teams to understand customer behavior and identify patterns and trends related to revenue churn
- Collect and integrate data from disparate sources such as Salesforce, proprietary billing systems, Oracle service cloud, and other databases
- Develop and implement predictive models using machine learning and statistical techniques to predict customer churn and revenue loss
- Work with large datasets using SQL and other database systems
- Conduct A/B testing and other experiments to validate and refine models
Other
- Currently pursuing a Master's degree in Computer Science, Mathematics, Statistics, or a related field
- Ability to work independently and as part of a team
- Excellent communication skills and ability to present findings to non-technical stakeholders
- Expected graduation year: 2025
- No travel requirements mentioned, no clearance requirements mentioned
