using sophisticated analytics and Machine Learning models to address difficult business challenges and generate departments to design data strategies, build models, and embed those models into software-driven business processes Feature Engineering, and Model Evaluation. DUTIES: Data Analysis and Modeling – Develop and deploy Machine Machine Learning and Artificial Intelligence models and algorithms to extract insights, predict outcomes data for modeling. Work with Data Engineering teams to ensure data availability and quality. Model Evaluation
Analysis and Modelling: Develop and deploy machine learning and artificial intelligence models and algorithms data for modelling Work with data engineering teams to ensure data availability and quality Model Evaluation Deployment: Evaluate model performance and fine-tune models for improved accuracy Deploy models in production Implement best practices for model version control and management Ensure proven models are integrated into business requirement for human intervention to implement the model within their respective businesses Cross-Functional
and control. Data Modelling Function: Maintain a competency of logical data modelling to depict business and modelling as well as general logical modelling concepts. Reverse and forward engineer models from subject matter experts. Educate the IT team using models, on the design impact from changes and developments
Create system design documents, including data models, flowcharts, and interface designs. Work closely methodologies and best practices. Proficiency in system modeling tools and techniques. Must be willing to travel
SSIS, SSRS: they use Power BI Relational database modeling Basic knowledge of database management Integration
that it can be translated into a specific data model Further refining the physical design to meet system
data collection, data cleaning and manipulation, model creation, analysis, and presentation of clients
that it can be translated into a specific data model Further refining the physical design to meet system
and data science teams to develop and deploy AI models that improve debt collection strategies and customer
that it can be translated into a specific data model Further refining the physical design to meet system