Quantitative Analyst at Nedbank

Job Purpose

• Advanced Analytics and Innovation has been established to serve as the Advanced Analytics Centre of Excellence (COE) focusing on advanced analytics, unlocking meaningful MI, increase efficiencies through automation and delivering high quality sustainable solutions, servicing the traditionally un-serviced areas while remaining a key contributor to the established modelling areas. Promoting and advocating for efficient change and innovation while ensuring that we change safely.
• The incumbent of the role is to apply advanced analytics techniques to drive innovation within the organization, contributing and enhancing the key focus areas of the team objectives. The role includes analysing complex problems, developing fit for purpose solutions and identifying insights to support decision-making and drive business growth.

Job Responsibilities

• Design and develop superior innovative quantitative solutions to service stakeholder and business requirements across the group (including AI/ML initiatives across clusters, Credit Risk, Financial Crime, People Risk (HR analytics), Compliance and Conduct Risk analytics, Group Internal Audit (GIA) through analysis; business requirements gathering and designs validation.
• Contribute towards multiple group wide strategic initiatives relating to AI and ML. 
• Model and methodology advisory and support for all clusters (solution generator, unlock business and client value).  
• Challenge model builds through expert group and model technical forum participation, contribute to the development of differentiated, superior solutions and ensuring best practice.
• Seek opportunities to improve business processes; models and systems by identifying and recommending effective ways to operate and adding value to Nedbank. 
• Build relationships with stakeholders by networking through targeted and informal interactions and consistent delivery of quality output to build trust. 
• Enhance applicable the group frameworks and policies, participating in annual review processes. 
• Increase efficiencies through programming and automating processes.
• Build and formally present reports by monitoring business performance within the set risk appetite and through analysis.
• Report to; monitor and advise operational areas to manage trends through analysis for ad-hoc requirements.
• Ensure personal growth and enable effectiveness in performance of roles and responsibilities through formal and informal learning activities and practical experience.
• Enable skilling and required corrective action to take place by sharing knowledge and industry trends with team and stakeholders during formal and informal interaction.
• Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.
• Contribute to a culture conducive to the achievement of transformational goals by participating in Nedbank Culture building initiatives (e.g. staff surveys etc).

Essential Qualifications - NQF Level

• Advanced Diplomas/National 1st Degrees
• Post graduate degree in mathematics/statistics/actuarial science/engineering/data science or a related quantitative discipline.

Preferred Qualification

• Post graduate degree in mathematics/statistics/actuarial science/engineering/data science or a related quantitative discipline. Master's degree is preferred.

Minimum Experience Level

• 1 year relevant of professional experience in an analytical and technical environment, with a focus on innovation and applying data-driven approaches to solve complex problems.

Technical / Professional Knowledge

• Business Acumen
• Microsoft Office
• Risk management process and frameworks.
• Strong analytical skills: Demonstrated ability to analyse large datasets, identify patterns, and draw meaningful conclusions. Experience with statistical analysis, data mining, and machine learning techniques is essential.
• Problem-solving mindset: Proven track record of identifying innovative solutions to business challenges using data-driven approaches. Ability to think critically, creatively, and outside the box.
• Relevant software and systems knowledge:
• Programming languages: Proficiency in one or more programming language commonly used in data science and quantitative analytics.
• Data analysis and visualization: Experience with data analysis libraries and frameworks. Familiarity with data visualization tools like Power BI is a plus.
• Machine learning: Strong understanding of machine learning algorithms and their applications. 
• Data manipulation and cleaning: Proficiency in data cleaning techniques, data pre-processing, and feature engineering. Experience with tools like for data manipulation is preferred.
•   Automation techniques: Experience in using advanced techniques and tools to automate processes.
• Model Governance: Knowledge of model governance principles and best practices, ensuring quality, integrity, and compliance throughout the model life-cycle.
• (Bonus) Credit process knowledge: Familiarity with credit assessment and evaluation processes in a business context. Understanding of credit risk modelling, credit scoring, and credit underwriting practices.
• Communication skills: Excellent verbal and written communication skills to effectively present findings and insights to both technical and non-technical stakeholders. Ability to explain complex concepts in a clear and concise manner (business writing skills).
• Collaboration skills: Ability to work collaboratively with cross-functional teams, such as credit analysts, business stakeholders, and IT professionals, to gather requirements and implement automated solutions effectively.

Behavioural Competencies

• Adaptability
• Applied Learning
• Earning Trust
• Communication
• Stress Tolerance
• Driving for results
• Continuous Improvement
• Technical/Professional Knowledge and Skills