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To develop and maintain best practice models and assessment strategies in line with regulations (where applicable) in order to facilitate world class risk management and/or attainment of strategic objectives.
Implement the financial crime analytics strategy across Group Risk
Build and establish a discipline of exceptional financial crime analytics, enabling stakeholders at making Nedbank world class at tackling financial crime
Use advanced analytics tools (such as machine learning, statistical techniques) to produce sustainable solutions to problems that the business needs to address.
Design, develop and implement data and analytics products that enable internal stakeholders to comply (i.e. improve compliance rate) to regulatory requirements and the bank’s policies.
Build algorithms and design experiments to merge, manage, interrogate, and extract financial crime data to create data and / or analytics products (tailored reports, dashboards) to colleagues, peers. customers or the wider organisation
Work with stakeholders across the bank to identify opportunities for leveraging Nedbank’s data to drive risk management solutions that address financial crime challenges within the organisation.
Work with stakeholders, to build and implement the most appropriate models that:
provide actionable insights on banks financial crime risk landscape,
optimise decision making to response to risks posed by financial crime incidents
anticipate the occurrence of financial crime incidents
mitigate the impact of financial crime incidents
Maximise the automation of financial crime analytics across the modelling cycle, leveraging existing infrastructure and resources.
Assist FCORA to create and maintain optimal data pipeline architecture that integrates use cases (project), prototyping and productionalisation of data and analytics products.
Assemble large, complex data sets that meet functional / non-functional business and risk requirements (e.g., alignment to Enterprise Data Programmes, etc.).
Ensure data security across all categories
Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure, where required, for greater scalability, etc.
Build the capability required for optimal extraction, transformation, and loading of data from a wide variety of data sources (including internal and external data) using big data technologies and capabilities.
Create data tools for analytics and data scientist team members that assist them in building and optimising our products to promote innovation and leadership in Financial
Crime Analytics across the Group, allowing for the utilisation of data pipelines in order to provide actionable insights.
Roles & Responsibilities
Model development and R&D
Conduct high quality research to proactively identify areas for improvement to reduce the risk of financial crime and recommending changes to procedures and standards where appropriate
Keep abreast with the latest trends in risk and financial crime analytics with the intention to enhance internal tools, models, and methodologies on a continuous basis
Apply mature and sound judgment in the selection of methods that provide a balanced approach to address both the theoretical and practical issues when faced with very
Research, present and resolve issues emanating from the implementation of financial crime models
Design, develop and deploy reporting dashboards for financial crime analytics
Ensure prudent governance of all financial crime models and analytics products
Ensure that all financial crime models and analytics products are compliant to internal policies and regulatory requirements.
Ensure that analytics data sets are governed and managed according to the bank’s policy (including RDARR / EDP)
Ensure transparency (documentation) and explainability of the analytics, models and reporting related to financial crime
Ensure provision of relevant, concise, accurate, reproducible, and timeous reporting to senior management and governance committees
Work with 2nd and 3rd lines of defence to ensure quality and reliability of the bank’s analytics and data products
Provide leadership in the various aspects of Nedbank’s financial crime and anti-money laundering program
Lead and manage projects related to financial crime analytics
Provide mentorship to graduates, colleagues and various stakeholders
Represent the bank in designated industry groups (SABRIC, etc.)
Participate and contribute to the formulation and execution of the FCORA strategy
Develop and maintain productive relationships with internal and external clients, stakeholders, and peers
Engage and explain “difficult” analytics concepts to clients and stakeholders across the Group
Ability to develop models with varying complexity that deliver actionable insights
Experience in supervised and unsupervised machine learning techniques
Experience with deep learning tools and techniques, such as NLP, would be an advantage
Ability to engineer features from sourced and existing data sets
Ability to translate business requirements into sustainable and robust analytics solutions
Able to translate model outcomes into understandable management information
Understanding of big data technologies including cloud computing facilities such as Azure and AWS
Understanding of data compression techniques to utilise Big Data
Understand database design, development, implementation, and management including optimisation thereof.
Able to develop and implement scalable frameworks in the context of data engineering and data science.
Building and optimising ‘big data’ pipelines, architectures, and data sets including automation
Understand and have knowledge Docker frameworks such as Kubernetes etc.
Experience with SQL / PostgreSQL / Data Views (Denodo).
Experience with object-oriented and functional scripting languages: Python, R, SAS, MATLAB, Spark, Java, C++, etc.
Use of any visualisation technologies (e.g., Power BI) will be advantageous.
Able to design, develop and implement bespoke applications and to deploy executables
Experience in system design, implementation, and optimisation – including use of the MVC design pattern.
Able to utilise bitbucket and any or similar git framework for code versioning and documentation
Able to manage stakeholders across the various levels of seniority
Essential: BSc / BCom / BEng with relevant Computer Science / Statistics / Mathematics focus
Preferred: Post graduate degree in Statistics / Mathematics / Computer Science
Type of Exposure
Analysing situations or data that requires an in depth evaluation of multiple factors
Developing ways to minimize risks
Managing conflict situations
Influencing stakeholders to obtain buy-in for concepts and ideas
Sharing information in different ways to increase stakeholders understanding
Comparing two or more sets of information
Working with a group to identify alternative solutions to a problem.
Interacting with diverse people
Building and maintaining effective relationships with internal and external stakeholders
Analysing and interpreting quantitative and qualitative data
Minimum Experience Level
3-5 years relevant experience in an analytical environment
Technical / Professional Knowledge
Principles of project management
Relevant regulatory knowledge
Relevant software and systems knowledge
Risk management process and frameworks
Business writing skills
Technical/Professional Knowledge and Skills
Note: Never pay for any training, certificate, assessment, or testing to the recruiter.
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