- Data is one of our greatest assets and how we harness it to understand the world, our business and our customers’ needs is crucial. In the Chief Data Office (CDO), we promote the intelligent use of data and make sure it is used in the right way to power our business decisions.
- Data science allows us to apply statistics, computer science and problem solving skills together with strong research methods to test, learn and optimize business processes.
- The role holder will be responsible for the use of statistics and machine learning models to solve complex business problems across various domains. This will involve working across various projects collaborating with the wider CDO team and an ability to provide clear updates to stakeholders and project managers.
- You will have a chance to get exposure to data science and how we deliver value to our customers while working as part of a team who will be guiding you throughout.
- Perform statistical analysis – through developing and deploying models on large data sets.
- Conduct exploratory data analysis and an ability to perform simple queries, aggregations, joins and transformations using SQL.
- Demonstrate an understanding of agile delivery.
- Evaluates user request for new/modified solutions to determine feasibility, time required, compatibility with current system and computer capabilities.
- Transform large complex datasets into pragmatic actionable insights that influence tangible business gain.
- Advice on data collection procedures to include information that is relevant for building analytic systems.
- Processing, cleansing, and verifying the integrity and quality of data used for advanced analysis.
- Doing ad-hoc data analysis and presenting results in reports, dashboards and charts.
- Challenge ideas and methods while working together with talented, highly skilled team members.
- Gather and process raw, unstructured data at scale into a form suitable for analysis.
- Improve data foundational procedures, guidelines and standards and develop best practices for data management, maintenance, reporting and security.
- Develop and maintain documentation/manuals on models developed, reports generated and statistical solutions devised.
- Carry out user training as required to enable users interpret Data Science solutions.
- Ability to take personal responsibility and accountability for timely response to client queries, requests or needs, working to remove obstacles that may impede execution or overall success.
- Assist in developing and implementing a program of continuous improvement of Data processes through a cycle of analysis of existing systems, processes, and tools, identifying areas for improvement, and implementing high-impact changes, and getting feedback from stakeholders.
- Understand Key Performance Measures and Indicators that drive company performance measurement, reporting, and analytics across functions and understand how these metrics and measures align and track against overall business strategies, goals and objectives.
- Work with business customers to understand business requirements and implement solutions and with business owners to develop key business questions and to build datasets that answer those questions.
Education and experience required:
- Bachelor’s degree in Mathematics/statistics, data sciences, computer science, economics or related quantitative fields is preferred (or equivalent on-the-job experience).
- NQF level no.
- A minimum of 1-2 years technical experience.
Knowledge and skills:
- Demonstrable interest in data science/analytics.
- Proven ability to collaborate with other team members and contribute productively to the team’s work and output, demonstrating respect for different points of view.
- Programming skills/concepts and the ability to pick up new technology with ease. Prior experience in R, Python, and/or other statistical tools and languages is a plus.
- Prior experience, in an academic or work setting, in one or some of – machine learning, data mining, unstructured data analytics, natural language processing, statistical or mathematical modeling.
- Familiarity with relational databases and an understanding of SQL are a plus.
- Understanding of a wide range of statistical techniques.
- Ability to understand and present finding to a wide range of audience.
- Prior experience in data visualization and an ability to derive insights is a bonus.
- An interest and understanding of machine learning techniques and algorithms, such as regression, k-NN, Naive Bayes, SVM and Decision Forests.
- Experience with or training in common data science toolkits, such as R, Python, Matlab, Julia etc.
- Demonstrable interest in using query languages such as SQL etc.
- Good applied statistics skills, such as distributions, statistical testing, Bayesian statistics etc.
- A demonstrable interest in cloud technologies such as AWS, Azure and GCP. Demonstrable experience is a plus.
Interested and qualified?