The retail company needs to forecast the order numbers of its delivery service to plan the personnel, logistics and marketing activities accordingly. As a second activity the existing customer segmentation will be revised, taking into account the contribution the profit margin of customers.
The bank is trying to build up a fraud scoring system in addition to the existing risk models. With a dataset of detected fraud cases, the bank wants to test in a PoC, if standard software solutions will lead to a better result than a “home-made” fraud-detection model.
Banks are looking to advanced data analytics to help them keep up with increasingly complex money-laundering techniques.
Analytics can be leveraged to identify suspect information, patterns and behaviors in different data sets, including customer information, accounts, and transaction data.
The goal of the project was to build a model which identifies suspect transactions.
A UK leading retailer wanted to forecast the demand of fresh food (5000 SKUs) for each store (3500) considering internal and external (e.g. weather, special events etc) data. 15 Mio forecasting models were build.
Using advanced analytics to identify fraudulent behavior in accounting systems to streamline the auditing process.
Project management for the development of a release of a software module.
The aim of the project was to identify primary variables as part of root-cause analysis for a repeating warranty case at a specific model. The project was able to find the causes and suggest an easy fix to prevent it in the future.
Building a model to predict an prevent churn of mobile phone customers.
Controlling
Mathematische Verfahren
Marktforschung
Consulting- und Managementerfahrung aus langjähriger Tätigkeit in Unternehmen (u.a. IBM, PwC)
The retail company needs to forecast the order numbers of its delivery service to plan the personnel, logistics and marketing activities accordingly. As a second activity the existing customer segmentation will be revised, taking into account the contribution the profit margin of customers.
The bank is trying to build up a fraud scoring system in addition to the existing risk models. With a dataset of detected fraud cases, the bank wants to test in a PoC, if standard software solutions will lead to a better result than a “home-made” fraud-detection model.
Banks are looking to advanced data analytics to help them keep up with increasingly complex money-laundering techniques.
Analytics can be leveraged to identify suspect information, patterns and behaviors in different data sets, including customer information, accounts, and transaction data.
The goal of the project was to build a model which identifies suspect transactions.
A UK leading retailer wanted to forecast the demand of fresh food (5000 SKUs) for each store (3500) considering internal and external (e.g. weather, special events etc) data. 15 Mio forecasting models were build.
Using advanced analytics to identify fraudulent behavior in accounting systems to streamline the auditing process.
Project management for the development of a release of a software module.
The aim of the project was to identify primary variables as part of root-cause analysis for a repeating warranty case at a specific model. The project was able to find the causes and suggest an easy fix to prevent it in the future.
Building a model to predict an prevent churn of mobile phone customers.
Controlling
Mathematische Verfahren
Marktforschung
Consulting- und Managementerfahrung aus langjähriger Tätigkeit in Unternehmen (u.a. IBM, PwC)
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