Administrator AND a Data Capturer - Cape Town (Paarl area) ADMINISTRATOR as well as a DATA CAPTURER Matric MUST MUST be Computer Literate Minimum 2-3 Year's working experience either as a: ADMINISTRATOR (Office) OR OR DATA CAPTURER Clean Criminal record - will be verified Monthly
Administrator AND a Data Capturer - Cape Town (Paarl area) ADMINISTRATOR as well as a DATA CAPTURER Matric MUST MUST be Computer Literate Minimum 2-3 Year's working experience either as a: ADMINISTRATOR (Office) OR OR DATA CAPTURER Clean Criminal record - will be verified Monthly
a
DATA CAPTURER
* Matric
* MUST be Computer Literate
ADMINISTRATOR (Office) OR
DATA CAPTURER
* Clean Criminal record -
/>Job Description:
Utilize Computer-Aided Engineering (CAE) software tools
Validate
Experience:
Advanced proficiency in computer applications, with a strong focus on advanced
Mechanical FEA Simulations Engineer
Cape Town
Minimum requirements and experience:
Responsibilities:
skills
Qualifications experience
and experienced Data Scientist with a robust background in data analysis, machine learning and R, as well as expertise in SQL for efficient data manipulation. Excellent problem-solving skills, exploring emerging technologies and methodologies in the data science field.Â
What you’ll do explore, examine, integrate and scrub data from multiple disparate data sources required to answer complex and collaborative partnerships with BI Analysts / Data Scientists / Use Case Owners in the business.
statistics, mathematics, operational research, economics, data engineering, risk management, or equivalent industry
1. Data Analysis: Analysing and interpreting complex data using statistical methods and tools to uncover insights and trends. 2. Data Extraction: Using ETL / ELT methods and tools like Azure Data Factory and Synapse Synapse. 3. Data Visualization: Creating visualizations and dashboards to communicate data insights effectively 4. Data Cleaning: Cleaning and preprocessing data to ensure accuracy and completeness. 5. Data Modelling: Working collaboratively with other members of the data science team and other departments to identify business