Senior Data Scientist at FNB South Africa

Job Description

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced
mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.

• Innovate by finding the best fit solution for the situation such as the flexibility of delivery and customized solutions which result in more efficient outcomes.
• Provide input into localisation of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Adhere to model building policies, standards, frameworks, and governance process.
• Ensure own ethical usage of information that complies to restrictions applied for privacy and sensitivity classification.
• Understand and ensure implementation and adherence to Privacy business requirements, legislation and policy.
• Ensure reporting of any Information Privacy Incidents and escalate appropriately for resolution of Privacy and Protection Audit Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Create delivery plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Analyse available data to identify information commercialisation opportunities that have not been explored to address business needs and revenue options.
• Productionize analytics in the approved FirstRand architecture by translating technical data information into practical business information that addresses identified needs.
• Analyse information requirements, availability and quality of data to feed into management for resolution.
• Contribute to the development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques and utilise as appropriate.
• Collaborate with numerous departments across the business to aid them in the proper use of data to ensure delivery of desired operational results.
• Participate in relevant project related to the business overall analytical needs and opportunities.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Build models that analyse processes to recommend areas for optimisation to achieve cost savings, revenue generation or efficiency improvements for the business.
• Document and audit relevant processes.
• Document and implement models to address specific business requirements.
• Conduct appropriate manipulation and analysis of data to pro-actively identify and meet needs of the business for the purpose of future work and to ensure high information-quality and reliability across the business.
• Apply own understanding of statistical techniques to determine approach to provide input required for decisions and design or evaluation of experiments.
• Apply technical concetps such as (Multivariable Calculus, Linear Algebra etc.) concepts to improve predictive performance or algorithm optimisation in data defined products.
• Implement Machine learning mathematical algorithms and automation techniques using open-source programming languages such as SAS or Python libraries.
• Utilise advanced Predictive modelling techniques to hold insight into outcomes and future events thatmconfront key assumptions.
• Utilise data to model complex abstractions in machine learning research to enable deep learning.
• Utilise pattern recognition technology to recognizes patterns in data and the criteria for use interchangeably with machine learning technology.
• Build and program own statistical model in statistical software for application development to productionize the model into a software application conducted by software developers.
• Conduct Text analytics to examine unstructured data to glean key business insights.
• Understand principles of Data Wrangling to identify and recommend corrective actions for imperfections in data quality.
• Participate in enterprise-wide high level problem resolution by interacting with relevant engineers and product managers, utilising appropriate methods and decide when approximations make sense.
• Conduct data visualisation to present data, findings and techniques to audiences, both technical and nontechnical in a pictorial or graphical format so it can be easily analyzed utilising principles of visually encoding data and communicating information.
• Maintain ownership of models through regular audits and updates to ensure relevance.
• Plan and perform regular model updates that capture evolving business complexity in current models.
• Challenge current models to ensure relevance and accuracy of outputs.
• Test outputs and accuracy of models to ensure relevance.
• Use data and analytic insights to provide input into improving customer experience through a better understanding of the customers context to identify monetization opportunities and monitoring implementation of business decisions to recommend enhancements utilizing statistical modelling and data analysis.
• Validate, interpret and create reports and presentations for data analytics management and relevant stakeholders.
• Review and assist more junior Quantitative Analysts with processes and models.
• Participate and contribute to a development culture where information regarding successes, issues, trends and ideas are actively shared.
• Build and sustain collaborative working relationships with relevant peers and stakeholders to achieve productivity synergies.
• Participate in specialist communities of practice and contribute positively to own and organisational knowledge improvement.
• Contribute to the development of a budget aligned to operational delivery plans, monitor effectiveness and report on variances.
• Build relationships that allow for the managing of expectations; the sharing of knowledge and diverse insights; and the creation of buy-in.
• Engage in cross-functional relationships to obtain and to provide work support.
• Take all necessary actions to ensure compliance with relevant statutory, legislative, policy and governance requirements in area of accountability.
• Ensure implementation of relevant policies, governance and practice standards across the business.
• Maintain expert knowledge on relevant legislative amendments, industry best practices and business's internal compliance procedures and requirements.
• Ensure compliance is adopted in terms of systems and procedures as laid out by business.
• Implement and provide input into the development of governance and compliance procedures and processes within area of specialization and identify risks.
• Determine the business questions that need be answered and determine appropriate analytics models for utilization.
• Source and prepare relevant data sources for analysis.
• Translate business requirements into tangible models utilizing own understanding of the business value of projects, models and processes.
• Develop and apply analytical algorithms and methods to build, test and implement advanced mathematical models and analytical solutions that address business problem, opportunities and improve business outcomes i.e. reduced risk and costs, increased profitability, optimized efficiency and to facilitate strategic decision-making.

Additional Requirements

• 5+ years in a similiar Data Scientist Role
• OCR 
• Python
• Machine learning (both theory and applied)
• Strong technical background (SQL, Big Data, SAS Viya, AWS, PySpark, Redshift, Graph/Neo4J, Bitbucket)
• Banking experience is a plus
• Delegation, upskilling and mentoring of junior staff.
• Ownership of projects
• Bachelor of Science Degree or any similar degree ( e.g. Engineering, Actuarial Science, Mathematics, Statistics)

End Date: August 20, 2025