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  • Posted: Aug 16, 2021
    Deadline: Not specified
  • Nedbank Group Limited is a bank holding company that operates as one of the four largest banking groups in South Africa. The company's shares have been listed on the JSE Limited since 1969. The group offers a wide range of wholesale and retail banking services through four main business clusters, namely Nedbank Corporate and Investment Banking, Nedbank Retai...
    Read more about this company


    Senior Quantitative Analyst

    Job Purpose

    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.

    Job Responsibilities

    • 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 

      • difficult choices

      • Research, present and resolve issues emanating from the implementation of financial crime models

      • Design, develop and deploy reporting dashboards for financial crime analytics

    • Analytics governance

      • 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

    • Excellent leadership

      • 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

    Preferred Experience

    • 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

    • Industry trends

    • Microsoft Office

    • Principles of project management

    • Relevant regulatory knowledge

    • Relevant software and systems knowledge

    • Risk management process and frameworks

    • Business writing skills

    • Microsoft Excel

    • Business Acumen

    • Quantitative Skills

    Behavioural Competencies

    • Applied Learning

    • Coaching

    • Communication

    • Collaborating

    • Decision Making

    • Continuous Improvement

    • Quality Orientation

    • Technical/Professional Knowledge and Skills

    Method of Application

    Interested and qualified? Go to Nedbank on to apply

    Note: Never pay for any training, certificate, assessment, or testing to the recruiter.

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