cutting-edge technology. Our client is seeking a Data Scientist with a strong background in machine learning to travel to the office daily. Responsibilities: Data Analysis and Modelling: Develop and deploy machine optimize processes Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable validate findings Data Strategy and Planning: Collaborate with stakeholders to define data-driven objectives objectives and formulate data strategies aligned with business goals Identify key performance indicators (KPIs)
system-related problems. Data Management: Download data from the ERP system as required. Ensure data integrity and extraction and handling. Reporting: Organize downloaded data into predefined templates. Generate and distribute stakeholders on a regular basis. Data Analysis: Perform ad hoc data analysis to support business decisions decisions and operational improvements. Present data findings in a clear and concise manner. R20 000 - Monthly
system-related problems.
database Considering both back-end organisation of data and front-end accessibility for end-users Refining design so that it can be translated into a specific data model Further refining the physical design to meet documentation, including data standards, procedures and definitions for the data dictionary (metadata) Controlling SQL replication and exporting & importing of data is essential Must be able to create MS SQL Logins
and data integrity. Assist in the implementation and upgrade projects of SAP B1, including data migration creation of complex spreadsheets, pivot tables, and data analysis tools. Qualifications: Bachelor's Degree skills, including formulas, macros, pivot tables, and data analysis. Excellent analytical and problem-solving Detail-oriented with a strong focus on accuracy and data integrity. Preferred Qualifications: SAP B1 certification
Number and data formats, advanced functions and formulas, mixed references, range names, data validation validation Data analysis and cleaning techniques Using charts Pivot Tables and Pivot Charts What-If Analysis
Number and data formats, advanced functions and formulas, mixed references, range names, data validation validation Data analysis and cleaning techniques Using charts Pivot Tables and Pivot Charts What-If Analysis
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matured states
Leading initiatives such as data classifications, POPIA compliance.
2
transmission of data through secure internet gateways
and encryption of electronic data
Manage
disposal of data through assigning
responsibility for ongoing storage and disposal of data in accordance
integration and development Robust understanding of data manipulation, interpretation, and presentation Education: Education: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence or related (Honours