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Pick n Pay Stores Limited, through its subsidiaries and associates, operates in the retail sector on the African continent.
Pick n Pay is the quintessential family store focused on the customer. Since 1967 when consumer champion Raymond Ackerman purchased the first few stores, the Ackerman family’s vision has grown and expanded to now encompass stores...
Read more about this company
This exciting opportunity exists in our Online Shopping Division in Cape Town. We are looking for a Marketing Data Analyst who will be tasked with analysing online data and identifying areas to optimize the performance of online marketing campaigns. You will be using data to make informed decisions to improve ROI on marketing campaigns, develop insightful reporting, as well as provide thoughtful and strategic recommendations. You will be working in a young, independent Marketing team for an On-Demand app for one of SA’s largest retailers and most loved brands.
Your area of focus would be specifically within Marketing & Sales, working on analysing data related to product sales, volume & value share, basket level data, campaign pitching and reporting for our brand partners as well as shopping habits and insights for the on-demand app.
3 years' experience in Data Science and Analytics
Experience with MySQL and Tableau, PowerBI and similar tools is essential
Working Knowledge of Microsoft Office Tools i.e. MS Office (Excel & Powerpoint )
Experience in tracking and reporting on campaign performance
Google Analytics, Marketing attribution platforms such as Appsflyer experience are advantageous
E-commerce / on-demand industry and FMCG and / or retail environment experience is advantageous
Digital Advertising experience is advantageous
Preference will be given to candidates with experience using a statistical language like Python or R to work with big data, draw insights, build prediction models and more
Need to be familiar with on-demand delivery industry and apps such as Uber, Taxify, Takealot, Superbalist.
Duties & Responsibilities
Sales Tracking and preparation of volume and value share reports across all grocery categories
Campaign pitches and post campaign reporting to assist with the selling of campaigns and media on the app
Insights on product and users shopping off the app, such as basket level data
Collecting data – Collecting and mining data from the company database and external sources
Cleaning data – Cleansing unstructured, messy or ambiguous data into user-friendly data sets
Analysing results – Using statistical tools, alongside analytical and logical skills, to analyse and interpret data, in order to determine how it translates to the business (e.g. does it indicate falling profits, increase of costs, decrease in customer spending etc.)
Identifying patterns – Pinpointing trends, patterns and correlations in complex data sets
Spotting anomalies – Identifying data which doesn’t fit normal patterns to highlight errors and other issues
Managing data systems – Monitoring the storage, availability and coherence of all stored data
Creating data visualisations – Translating raw data into clear and concise images, charts and graphs
Preparing reports – Summarising and presenting data in clear, concise and actionable reports for stakeholder meetings and marketing material
Troubleshooting – Troubleshooting and resolving complex data issues within company systems
Determining goals – Working with management and relevant departments to determine the organisation’s data goals
Contribute to the overall success of the business by playing an active role in the leadership team
Actively work with others in the business to develop strategies and plans to execute major projects