Internship Customer Segmentation and Profitability Analysis using Advanced Analytics
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Job Location:
Amsterdam - Netherlands
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
The team
Value Reporter Customer profitability solutions - Traditional methods of analysing customer value often look backward calculating historical profitability or using generic segmentation (e.g. sectors product usage) that may not reflect future profit potential. The Finance Business Advice (FBA) team will benefit using a predictive tool to forecast each customers profit margin over the next year and to classify customers into segments based on predicted profitability and behaviour.
Moreover existing segmentation approaches might overlook critical cost factors for example customers who frequently use services might appear valuable by revenue but could actually yield lower profit once costs are considered.
Problem Statement
The core problem is twofold:
How can we accurately forecast a customers profit margin for an upcoming period using historical data and advance analytics How can we use these forecasts (along with behavioural data) to segment customers in a meaningful way that highlights differences in profitability and supports strategic decision-making
Objectives
- Develop a predictive model to estimate customer profit margin for the next year.
- Create customer segments based on predicted profitability and behavioral attributes.
- Provide actionable insights to help the company proactively manage high-value and low-margin customers.
Research Questions
- To what extent can historical customer data predict a customers future profit margin
- Which machine learning techniques are most effective for forecasting customer profit margin in this context
- How can predicted profitability and customer behavioral attributes be used to segment customers into meaningful groups
- What are the characteristics of the resulting customer segments in terms of profitability patterns and behaviors
- How can the outcomes of profit margin forecasting and customer segmentation be applied to drive business value
Methodology
- Collect and preprocess historical customer sector product organization performance category Country and financial data.
- Build predictive models (e.g. regression ensemble methods) for profitability forecasting.
- Apply clustering techniques (e.g. K-Means Hierarchical Clustering) for segmentation.
- Validate models using metrics like RMSE for prediction and others scorings for clustering.
Expected Outcomes
- A predictive tool for estimating customer profitability.
- Segmentation framework that highlights differences in profitability and cost structures.
- Strategic recommendations for managing customer relationships.
Rewards and benefits
This is a great opportunity to train with highly skilled people who are experts in their field. Youll do a lot and learn a lot not only about your specialist area and the bank but also about yourself and whether this type of environment is right for you.
Youll also benefit from:
Internship allowance of 700 EUR based on a 36 hours work week
Your own work laptop
Hybrid working to blend home working for focus and office working for collaboration and co-creation
Personal growth and challenging work with endless possibilities
An informal working environment with innovative colleagues
During the duration of your internship at ING it is mandatory to be enrolled at a Dutch university (or EU-university for EU passport holders).
Applications
Want to apply directly Please upload your CV and motivation letter by clicking the Apply button.
About our internships
Every year more than 350 students join our internship program. While there are no guarantees about your future many of our former interns move into a permanent role or onto our International Talent Programme (traineeship).
Whatever happens an internship at ING is the ideal opportunity to meet a wide variety of people to build up your own network and to learn about many different aspects of banking put simply its a great start to your career.
Required Experience:
Intern
Key Skills
- Adobe Analytics
- Data Analytics
- SQL
- Attribution Modeling
- Power BI
- R
- Regression Analysis
- Data Visualization
- Tableau
- Data Mining
- SAS
- Analytics
About Company
ING Global Career Opportunities - Welcome to 'careers at ING'. We give you the space to develop yourself as an intern, trainee and professional. Check out our opportunities. Jump on!
