Statistical DATA ANALYST – provide CONSUMER INSIGHT to support PRODUCT INNOVATION in E-COMMERCE/ ONLINE RETAIL – CAPE TOWN, R500K-R540K
This is an excellent opportunity for a QUANTITATIVE Statistical DATA ANALYST to be the heart of DATA ANALYSIS within the fastest growing E-COMMERCE / ONLINE RETAILER.
Based in CAPE TOWN this DATA ANALYST role offers a salary of R500K – R540K/annum.
This E-COMMERCE Business has established itself as one of fastest growing ONLINE RETAILER across the African market.
You will join a PRODUCT DEVELOPMENT Team – where your primary function will be to deliver cutting-edge CONSUMER INSIGHT in order to help understand the success of the current Products and to support innovation around new products in-line with consumer behaviour.
Key focus areas include:
Build and track Funnels,
Measure consumer conversion rates, and drop-offs,
Build visualisation from Product analytics data,
Mine product analytics data for insights.
This DATA ANALYST role provides you the opportunity to be the be the heart of product data analysis; mine data for insights, test and validate hypotheses about customer behaviour and demonstrate how product enhancements can delight customers.
You will be tasked with finding those hidden insights within exceptionally large Data sets, applying your data mining, and statistical analysis skills to communicate your insights back to senior execs thereby helping guide decisions about new initiatives to address consumer requirements.
You are likely to be degree educated in a subject with a strong numerical and data analysis component.
At least 3 years experience within quantitative statistical data analysis.
Ability to provide relevant insights and communicate those to senior level execs,
Strong ability to analyse and provide insight reports, using a range of data streams including web and app data sets.
Understanding of A/B testing, funnel building with large datasets and optimisation on digital platforms.
TECHNICAL SKILLS required: SQL, Google BigQuery, Firebase/Google Analytics, and Google Data Studio.