Senior Manager: Modelling & AI at Nedbank

Nedbank Group is a financial services group in South Africa offering wholesale and retail banking services as well as insurance, asset management, and wealth management. Nedbank Limited is a wholly owned subsidiary of Nedbank Group.

Job Overview 

• To lead and grow a high-performing team focused on advanced Machine Learning (ML) modelling and artificial intelligence capabilities that drive strategic value across the organization.
• This role is accountable for the development and operationalization of cutting-edge AI solutions, including predictive modelling, and generative AI.
• It enables scalable, reusable, and ethical AI practices by fostering cross-functional collaboration, embedding robust governance, and aligning with enterprise-wide data and digital strategies.

Responsibilities

• Define, grow, and lead a team of Data Scientists and ML Modelling Experts across proficiency levels, fostering technical excellence, delivery discipline, and innovation.
• Develop and deploy traditional ML models across key financial services domains fraud detection, collections, AML, operations, etc; using techniques like regression, classification, clustering, and time-series analysis to support decision-making and regulatory compliance.
• Advance customer and business intelligence through behavioural modelling, segmentation, lifetime value prediction, churn modelling, and recommendation systems — leveraging ensemble methods, graph-based learning, and temporal feature engineering to drive personalization and strategic growth.
• Explore and integrate advanced modelling approaches, including deep learning, graph neural networks, and retrieval-augmented generation (RAG) models — to enhance model performance, enable contextual understanding from unstructured data, and support emerging use cases such as document intelligence and GenAI-assisted analytics.
• Apply specialised ML techniques such as computer vision, natural language processing (NLP), and large language models (LLMs) to solve domain-specific challenges — including document classification, KYC automation, sentiment analysis, and intelligent customer interaction across banking channels.
• Identify opportunities across the Nedbank Group to enhance model performance and scalability through foundational capabilities such as feature engineering, graph-based data representation, and reusable modelling assets.
• Apply financial services domain knowledge to ensure models are aligned with regulatory requirements, business priorities, and industry-specific data characteristics.
• Collaborate closely with internal stakeholders — including business, data science, engineering, and platform teams — to ensure modelling solutions are integrated, governed, and strategically aligned.
• Introduce and support GenAI capabilities, particularly retrieval-augmented generation (RAG) models, where they complement traditional modelling — e.g., enhancing model explainability, document summarization, or contextual data retrieval.
• Design and manage data pipelines that support both traditional ML and GenAI workflows, including real-time and batch feature computation from structured and unstructured data sources.
• Drive innovation in feature creation, leveraging advanced techniques such as graph-based feature extraction, temporal feature engineering, and embedding generation.
• Lead the implementation and operation of scalable, reliable, and governed modelling platforms, ensuring they are production-ready, secure, and aligned with business needs.
• Own the lifecycle of modelling assets — including availability, documentation, versioning, monitoring, and governance — to ensure high-quality, trusted inputs for ML and AI solutions.
• Solve complex, unstructured problems with a detail-oriented mindset, working independently and driving initiatives to completion.
• Possess strong business and communication skills, enabling effective collaboration with business owners to define key modelling needs and ensure foundational assets meet those needs.
• Manage financial and business results, ensuring delivery within budget and timelines, and compliance with divisional billing and cost recovery processes.
• Deliver high-quality modelling systems and processes aligned to Nedbank’s strategic goals, data strategy, and AI roadmap.
• Provide timely, professional advice and strategic input to stakeholders, ensuring delivery within agreed quality, budget, and time parameters.
• Build and maintain strong stakeholder relationships by delivering consistent, high-value modelling services and solutions.
• Actively engage with clients, partners, and internal teams to build trust, align expectations, and ensure delivery of best-practice modelling foundations.
• Promote knowledge sharing and collaboration across teams and departments to strengthen the modelling and AI capability.
• Operationalize divisional strategy by aligning team priorities and empowering first-line managers with clear roles, performance measures, and delivery goals.
• Leverage professional frameworks, tools, and technologies to deliver scalable, strategic modelling solutions.
• Manage multiple foundational modelling assets through strategic planning, implementation, and continuous improvements

Qualifications

• Advanced Diplomas/National 1st Degrees
• Tertiary Qualification/ formal accreditation in STEM related field
• BSC Computer Science, BSc Engineering, Econometrics, Mathematical Statistics, Actuary Science.
• Masters or Doctorate will be an added advantage.
• Post graduate management qualification/MBA

Certifications

• ITIL Talent nurturing or equivalent MMP/SMP / MM or equivalent

Experience

• Minimum 6 to 8 years Data Science experience with 1-2 years management experience

Knowledge

• Deep understanding of Machine Learning, Statistics, Optimization, or related fields, with a strong emphasis on feature engineering, data representation, and model architecture design tailored to financial services use cases.
• Proficiency in Python (required), with experience in additional languages such as R, Scala, or Java being advantageous for integrating with enterprise systems and legacy platforms.
• Demonstrated experience applying machine learning foundations within the financial services sector, with a strong understanding of domain-specific data, regulatory considerations, and business drivers across risk, fraud, customer intelligence, and operational modelling.
• Experience working with large-scale datasets and distributed computing tools (e.g., Spark, Ray), particularly for feature computation, transformation, and scalable model training.
• Proven track record in delivering end-to-end ML use cases, with a focus on foundational components like feature stores, graph-based data structures, and reusable modelling assets.
• Hands-on experience with GenAI and retrieval-augmented generation (RAG) models, including the use of vector databases, embedding models, and prompt engineering to support document intelligence, contextual search, and hybrid ML-AI workflows.
• Ability to translate complex data concepts into business-relevant narratives and insights, enabling strategic decision-making and stakeholder alignment.
• Excellent written and verbal communication skills, with a strong ability to collaborate across cross-functional teams including data engineering, business, and platform stakeholders.
• Experience in budgeting, business administration, and strategic planning, with a focus on aligning modelling initiatives to divisional and enterprise goals.
• Knowledge of change management and client service management principles, ensuring smooth adoption and integration of modelling solutions.
• Familiarity with governance, risk, and controls, especially in the context of data and ML asset management, model risk, and regulatory compliance.
• Strong stakeholder management and influencing skills, with the ability to navigate complex organizational structures and drive consensus.
• Experience in employee development, talent management, and workforce planning, fostering a high-performance modelling team.
• Understanding of project management principles and relevant regulatory frameworks, including POPIA, Basel, and IFRS where applicable.
• Skilled in business writing, management reporting, and communication strategies, supporting executive-level engagement and reporting.
• Familiarity with the System Development Life Cycle (SDLC), ITIL, and IT architecture, ensuring modelling solutions are aligned with enterprise technology standards.
• Experience with graph databases (e.g., Neo4j, TigerGraph) and graph analytics, particularly for feature engineering and relationship modelling in financial datasets.
• Understanding of IT asset management processes and joint application development practices, supporting scalable and governed modelling infrastructure.
• Ability to work within and influence complex organizational structures, driving strategic modelling initiatives across multiple squads and domains.

Competencies

• Building Partnerships
• Facilitating Change
• Inspiring others
• Business Acumen
• Building partnerships
• Driving for Results
• Selecting Talent

Method of Application

Meet the qualifications?

Apply now at Nedbank on jobs.ned­bank.co.za