This is an excellent opportunity for a DATA SCIENTIST to support product, credit, sales, leadership and marketing teams with insights gained from analysing company data.
Based in CAPE TOWN this DATA SCIENCE role offers a salary of R60K – R65K/month.
Ideally, you will be adept at using large data sets to find opportunities for product and process optimisation and using models to test the effectiveness of different courses of action. You must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You’ll also have a proven ability to drive business results with your data-based insights.
You must be comfortable working with a wide range of stakeholders and functional teams.
Overall you will have a passion for discovering solutions hidden in large datasets and working with stakeholders to improve business outcomes.
Based in CAPE TOWN this is an established consumer-market business. Within both the FMCG and Financial Services industry they have maintained a leading position as a result of their appreciation of their data assets and their ability to interpret these to the benefit of company strategy development.
Work with stakeholders to identify opportunities for leveraging company data to drive business solutions.
Mine and analyse data from company databases to drive optimisation and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to data sets.
Use predictive modelling to increase and optimise customer experiences, revenue generation, ad targeting and other business outcomes.
Develop company A/B testing framework and test model quality.
Develop processes and tools to monitor and analyse model performance and data accuracy.
Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
A drive to learn and master new technologies and techniques.
Experience manipulating data sets and building statistical models.
Degree in Statistics, Mathematics, Computer Science or another quantitative field.
Knowledge and experience in statistical and data mining techniques.