Project type
Customer
Customer projects focus on understanding and improving how organisations interact with their customers. This includes measuring customer behaviour, identifying risks in customer relationships, and making better use of customer data. You find these projects at banks, retailers, e-commerce companies, and digital platforms.
In this type of project, you work with customer and transaction data to answer questions about behaviour or risk. That might mean building a model to predict which customers are likely to churn, identifying suspicious transactions, or measuring the effect of a marketing campaign.
Organisations need to understand their customers to grow revenue, reduce risk, and meet regulatory requirements. Customer projects provide that understanding through data. Some focus on commercial questions: which customers are likely to buy, which campaigns are working, and where customers are dropping out. Others focus on risk: which transactions are suspicious, and which accounts need closer monitoring.
The daily work varies by project type. On commercial projects, you build models that predict customer behaviour or measure the effect of marketing activities. On risk-focused projects, you build detection models and evaluate how well they identify suspicious cases. In both cases, you work with large datasets of customer and transaction records.
The shared tools are Python and SQL. Statistical methods are important for measuring effects correctly, and machine learning is commonly used for scoring and prediction. Privacy is a relevant constraint across all customer projects, since the data involved is personal and subject to GDPR. The work connects to roles such as Data Analyst, Data Scientist, and Risk Manager.
Customer projects
7 projects - select a phase to explore them.
Companies
Organisations where econometrics graduates typically work on Customer projects.
