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
exposed to a variety of disciplines and projects. Training – World class learning and problem solving concepts Stipend: R 10,000 per month The post Graduate Trainee Data Analyst appeared first on freerecruit.co.za .
successful creative itineraries and proposals Capture and confirm bookings in Tourplan Negotiate with series, and FIT booking Participate in supplier training and workshops Reduce the transaction turnaround
through creating customer confidence, capturing customer data, and building brand loyalty. Maintain up confident self-leader Actively participate in required training and education. This role routinely uses standard experience in a related field OR industry-recognized training or education in a related field. Requirements:
administration duties (reception, filing, faxing, data capturing, typing, opening of client files, correspondence
methodologies Conducts daily cycle counts and capturing figures Allocates stacking in the warehouse Maintain
will include, but not limited to; Assisting of Capturing of supplier invoices Handling all supplier RFC’s
develop personalized insurance. All clients to be captured on the CRM system. Duties/Responsibilities: • improvement and recommend appropriate solutions. • Capture all client information & maintain accurate
experience as an electrician, or quote estimator or capturer as per responsibilities below 2. Must have basic equipment) to ensure optimum use 13. Assist with training or coordination thereof as maybe requested from
involve adjusting product placement based on sales data and customer feedback. Promotions and Pricing: Collaborate merchandising initiatives. This may involve conducting training sessions or providing product knowledge support support to store staff. Sales Analysis: Analyze sales data and performance metrics to evaluate the effectiveness areas for improvement. Use insights gained from data analysis to make adjustments to merchandising plans