machine learning, statistical and mathematical models to solve business problems and enable the effective data by utilising cutting-edge technologies and model data preparation.
Responsibilities:
efficiency and availability.
SAC.
Data Modelling and data engineering skills.
SAP BW 7.5 Data Modelling and BEX skills
SAP BW4/HANA Data Modelling skills
SAP BW4/HANA Query Modelling skills
Any additional
responsibilities assigned in the Agile Working Model (AWM) Charter
ADVANTAGEOUS SKILLS
machine learning, statistical and mathematical models to solve business problems and enable the effective technologies and model data preparation. Responsibilities: Build statistical models Manage the development Define strategy to enable business use of predictive models Manage controls to enable risk monitoring Implement validate the effectiveness of the models Monitoring/Calibration of models Effective self-management and teamwork
efficiency and availability. Investigate all modelling and control system failures and associated deviations systems: Heat transfer modelling (finite element heat transfer Level 2 model) and combustion systems Rolling modelling (Level 2): Speed, temperature, forces, torques and flatness control models (including principle models for heating and rolling technology. Knowledge of how these Level 2 models are automatically
efficiency and availability. Investigate all modelling and control system failures and associated deviations systems: Heat transfer modelling (finite element heat transfer Level 2 model) and combustion systems Rolling modelling (Level 2): Speed, temperature, forces, torques and flatness control models (including principle models for heating and rolling technology. Knowledge of how these Level 2 models are automatically
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
vulnerabilities. Develop and maintain fraud detection models that are both accurate and minimize disruptions Optimizing Detection Models: Continuously review, analyze, and improve core models used to detect fraud legitimate transactions. This involves adjusting models and thresholds based on factors like desired alert Integrate new data sources when needed to improve model effectiveness. Assist data engineering efforts to data analysis. Experience applying statistical modelling techniques to solve complex problems. Familiarity
deploying BI solutions (e.g., data warehousing models) and creating visualizations and reports for requested in SQL, SSRS, Excel Work with the team in data modelling, database design, creating efficient SQL for fast Production experience working with at least modern modelling tools - on premise and / or in the cloud (e.g Analytics) Production experience working with DAX modelling measures (e.g. Power BI, Analysis Services, DAX
deploying BI solutions (e.g., data warehousing models) and creating visualizations and reports for requested SSRS, Excel