|Location||Johannesburg, South Africa|
|Date Posted||Sep 15, 2020|
- Oversee data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and
analyse phenomena. Model complex business problems, discovering insights and opportunities through statistical,
algorithmic, machine learning and visualisation techniques, working closely with clients, data and technology teams to turn data into
critical information used to make sound business decisions. Oversee predictive modelling.
Oversees business integration through integrating model outputs into end-point production
systems, where requirements must be understood and adopted relating to data collection,
integration and retention requirements incorporating business requirements and knowledge
of best practices.
Oversees the gathering of data for use in Data Science models, ensuring that chosen
datasets best reflect the organisations goals. Oversees data pre-processing including data
manipulation, transformation, normalisation, standardisation, visualisation and derivation of
new variables/features. Utilises advanced data analytics and mining techniques to analyse
data, assessing data validity and usability; reviews result to ensure accuracy, communicates
results and insights to executive leadership.
Guides and validates the design of various complex mathematical, statistical, and simulation
techniques to answer critical business questions and create predictive solutions which drive
improvement in business outcomes. Drives analytics and insights within required business
unit by developing advanced statistical models and computational algorithms based on
Codes, tests and maintains scientific models and algorithms; identifies trends, patterns, and
discrepancies in data; and determines additional data needed to support insight. Processes,
cleanses, and verifies the integrity of data used for analysis.
Presents results and recommendations to executive leadership and influences future
business plans based on insights using excellent communication, presentation and
Supervises and oversees the mining of data using state-of-the-art value extraction methods.
Enhances data collection procedures to include information that is relevant for building data
Liaise and collaborate with the entire Enterprise Data Office, providing support to the entire
department for its data science needs. Collaborate with subject matter experts to select the
relevant sources of information and translates the business requirements into data
mining/science outcomes. Supports an executive leadership by identifying and applying best
practices in field of advanced analytics (statistics, operations research, etc.) across the
Acts as a subject matter expert from a data science perspective and provides input into all
decisions relating to data science and the use thereof. Educate the organisation on data
science perspectives on new approaches, such as testing hypotheses and statistical
validation of results. Validates and certifies the work of other data scientists and trains team
members in statistical models and guides junior colleagues or less experienced staff on
projects and drives leading practice.
Develops, implements, monitors and maintains a comprehensive operational IA plan, rules,
methodologies and coding initiatives in order to drive IA for remediation efforts. Develops and
co-ordinates a comprehensive strategy for productionalising automation software so that it is
accurate and well maintained.
Risk, Regulatory, Prudential & Compliance
Guides the data management and modelling infrastructure requirements and monitors the
implementation thereof through the organisations infrastructure development processes,
adherence to the organisations model production processes, including UAT. Ensures
adherence to governance processes to manage the ongoing enhancement and maintenance
of business rules. Conducts regression testing across all relevant systems as required.
Overseeing activities of the junior team members, ensuring proper execution of their duties
and alignment with the organisations vision and objectives. Provide oversights and expertise
to the Data Science team. Required to draw performance reports and strategic proposals
form his gathered knowledge and analyses results for senior executive leadership.
Technology & Architecture
Builds machine learning models from and utilises distributed data processing and analysis
methodologies. Competent in Machine Learning programming in R or Python, with
supplementary still in Matlab, Java, etc. Familiar with the Hadoop distributed computational
platform, including broader ecosystem of tools such as HDFS / Spark / Kafka.
Preferred Qualification and Experience
Post Graduate Diploma - Information Studies
Post Graduate Degree - Information Technology
Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Teradata, Qlikview; Tableau, Python, C#, Java, C++, HTML
8-10 years - Proven development experience in software / software engineering.Â Â Up to date with developments in IAfield.Â Â Experience in technical business intelligence; in depth understanding of the banks data processes, systems and products. Knowledge of IT infrastructure and data principles forming the basis for data quality management. Project management experience. Exposure to data governance and regulatory matters. Experience in building models (credit scoring, propensity models, churn, etc
8-10 years - Experience in working with unstructured data (e.g. Streams, images)Understanding of dataflows, data architecture, ETL andprocessing of structured and unstructured data.Using data mining to discover new patterns from large dataseImplement standardand proprietary algorithms for handling and processing data. Experience with common data science toolkits, such as SAS, R, SPSS, etc.with data visualisation tools, such as Power BI, Tableau, etc.