Henkel
Software Engineer
Project description
The service is requested as part of the project Customer 360 Pilot and the purpose is as follows:
Using advanced data analytical methods, deep diving into Adhesive sales projects to dig out and build customer turnover logic, product recommendation system, business optimized win/loss forecast model, optimized customer turnover prediction model and advanced authorization concept for the dashboard and guide sales team for more effective project management, in order to drive customer & sales momentum. After that, creating a reporting web & mobile application which is embedded to SAP/ACE system.
Task Description
The scope of services includes the following tasks, which are independently performed by the external contractor:
Building a recommender system using a Machine Learning algorithm of their choice in industry to provide a Power BI dashboard which is embedded to Henkel’s SAP system for sales representatives in order to recommend a product for sales;
Using Python (PySpark) to connect financial data which is provided by the Henkel Data Foundation (HDF) to the Machine Learning algorithm;
In case further data is needed for the large-scale machine-learning models (recommender system model), establishing a data pipeline which can be connected to HDF and Dremio.
The service provision of the contractor has the goal to establish a recommender system usable for sales representatives that can be connected to Henkel data sources through pipelines.
Timelines / Timelines
This project has an estimated Go Live in June – tasks should be finalised until the end of May.