Senior Data Scientist

Permanent

Cape Town (hybrid / flexible but needs to be in Cape Town) 

A Digital Media & Technology company has been established to accelerate the use of data in improving customer experience and business operations.

The company has been set up to work in an agile way, with center's of excellence as well as product focused teams. The team has a few senior roles for experienced Data Scientists within key product teams as well as within the centers of excellence.

In this role you will be involved in creating opportunities that delight our customers by leveraging the larger enterprises vast operational data. Using this data with predictive modelling you will have a direct impact on strategic initiatives to be truly customer centric.

The environment you will work in is highly entrepreneurial, you will be expected to deal with a high level of ambiguity and building to ensure that we are able to achieve our vision. We are focused on becoming a high-performance organisation that attracts the finest talent to make a difference to our customers.

You will work with Retail Media, Insights & Data Monetisation, Rewards & Personalization, Digital Commerce, & Customer Innovation 

Role Objectives

Work in a cross-functional team, collaborating with fellow data scientists, engineers, and analysts to understand project goals, interpret end-users' intent and drive the build, implementation and scale-up of use cases for measurable impact. Use your depth of knowledge and experience of data science concepts (linear and logistic regression, SVM's, dimensionality reduction), decision trees, gradient boosting, ensemble models, etc. to develop and lead the development of value-centric machine learning solutions. Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests. Collating and cleaning data from various entities. Working together in a squad of business representatives, Data Analysts and Data Scientists to realize the successful completion of projects. Selecting and employing advanced statistical procedures to obtain actionable insights. Cross-validating models to ensure their generalizability. Producing and disseminating non-technical reports that detail the successes and limitations of each project. Suggesting ways in which insights obtained might be used to inform business strategies. Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.