56 Nlp Engineer jobs in South Africa

Not for First Time Job Seeker

Important:
This role requires all 12 listed skills.

Please ensure your CV clearly reflects each of these with traceable experience and references. Candidates missing any of the required skills will not be considered.

JOB ROLE - DATA SCIENCE/ AI/ML Engineers:-

Educational qualifications

• Bachelor's degree in data science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• Master's or PhD in Machine Learning, Applied Mathematics, Econometrics, or AI (strongly preferred).

SKILLS:

Machine learning engineering

Azure databricks

Business acumen

Python

SQL

Version control and collaboration tools (git, azure repo)

Strong communication with non-technical stakeholders

Cloud platform knowledge (azure)

Model deployment (CI/CD pipelines, model monitoring)

Understanding of rag pipelines and autonomous agents

Feature and ml data engineering (advanced big data wrangling)

Understanding of project management and agile methodologies

Relevant experience

• 8–12 years of experience in data science, machine learning, or advanced analytics roles, with at least 3 years in a leadership or managerial capacity.
• Proven delivery of AI/ML models in production environments—preferably in Fintech, Banking, or Telecoms.
• Experience translating complex data science solutions into measurable business outcomes (e.g., credit scoring, fraud detection, churn prediction).
• Exposure to cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI)."

Required certifications

Preferred: TensorFlow, AWS ML Speciality, Microsoft AI Fundamentals

Key responsibilities

• Lead and scale a high-performing team of data scientists and ML engineers.
• Define and execute the data science roadmap, aligned to business priorities and monetisation opportunities.
• Oversee the end-to-end model lifecycle—from ideation, exploration, development, validation, to monitoring.
• Partner with Product, Risk, and Engineering to integrate models into digital and operational channels.
• Establish standards for model governance, explainability, and ethical AI practices.
• Drive innovation by exploring emerging techniques in generative AI, reinforcement learning, and real-time scoring.

Work location

Hybrid

Contract Position

Job Description
Hello Data Science Manager. Welcome to FNB, the home of the #changeables. We design for the shapeshifters and the game changers. As part of our talent team at FNB Personal Core Banking, you will be surrounded by unique talents, diverse minds, and an adaptable environment that lives up to the promise of staying curious. Now's the time to imagine your potential in a team where experts come together and ignite effective change.

The Personal and Private Core Banking Pricing team is a centre of excellence for FNB. They perform the formulation and execution of pricing strategies across the various business units including Personal Core Banking, Private Core Banking, Credit Card, Home Loans, FNB Channel Islands and Broader Africa. This crucial function engages many senior stakeholders including our CEOs, CFOs and Product Heads to collaboratively drive revenue and income statement growth. The team consists of passionate driven individuals who are invested in the team's success and work together to drive towards outcomes that exceeds expectations.

We're looking for a seasoned Data Science Manager to revolutionize our data utilization. You'll be responsible for building, optimizing, and implementing innovative quantitative analytical methodologies, procedures, products, and advanced mathematical models for our Business Pricing Model. You'll provide analytical support and interpret insights to address business opportunities and problems and implement business strategy with minimal guidance. You'll manage an analytics team, streamline processes, and ensure compliance with privacy requirements. Your role includes integrating analytics into operations, developing core capabilities, and driving performance. Join us to lead data-driven strategies and enhance our business outcomes.

Are You Someone Who Can

• Manage Quantitative Analytics and Modelling team (5 + team members)
• Ensure adoption and localization of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Establish goals and strategies for area of accountability in collaboration with senior data analytics management.
• Ensure 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 drive resolution of Privacy and Protection Audit.
• Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Provide and use data and analytic insights to improve customer experience through a better understanding of the customers context to identify monetization opportunities.
• Manage analytics team in the creation of high-quality analyses for all functions of the business, across area of accountability.
• Create tactical plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Drive team performance of analytics solutions; drive and enhance data systems and streamline business processes to impact overall business results while keeping costs in check.
• Analyse available data to identify information commercialization opportunities that have not been explored to address business needs and revenue options.
• Ensure analytics productionization 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 Data and information management function and forums for resolution.
• Oversee the appropriate manipulation and analysis of data for to meet needs of the business for the purpose of future work and to ensure high information-quality and reliability across the business.
• Integrate analytics into operational processes to improve efficiency and client experience.
• Ensure development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques.
• Manage overall project dependencies management and long-term prioritization of the business's overall analytical needs and opportunities.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Define the business questions for Business unit that need be answered; define appropriate analytics models in addition to identifying and readying relevant data sources for analysis.
• Address business problems and opportunities through robust underlying analytics.
• Translate business requirements into tangible solutions or models utilizing own understanding of business value and interrelated nature of projects, models and processes.
• Ensure accurate development and application of 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.
• Provide requirements to Business Information.
• Management Function as Supplier or Owner of Data to ensure data is prepared for consumption as an organizational asset.
• Create team tactical plans for achievement of outputs or deliverables in collaboration with Technology stakeholders to ensure the effective implementation of analytical solutions and models to support business requirements.
• Ensure governance and compliance rules are followed in application and implementation of predictive models to enable the business to manage risk.
• Maintain ownership and oversee the implementation of models.
• Monitor output and accuracy of models.
• Ensure the documentation and auditing of relevant models, projects and processes.
• Provide input into business strategies through data analysis that proactively improve efficiency, identify risks, save costs and drive innovation.
• Lead business through efforts that drive business performance and potential by using the existent and new data sources and techniques.
• Enable business unit to understand its own health, finds growth levers, and identify opportunities for optimization.
• Create new data-driven approaches for the purpose of generating business insights through data analytics, information visualization and addressing unanswered business issues in a proactive manner.
• Ensure validation and interpretation of analytical results and creation of reports and presentations for data analytics management, departmental heads/management, and relevant stakeholders.
• Collaborate with numerous departments across the business to assist in the proper use of data that ensure delivery of desired operational results.
• Model and drive a data driven culture that values data as an asset with business value.
• Lead relevant change and communications functions to drive functional maturity.
• Manage people by executing management responsibilities and create an environment that encourages employee growth and performance excellence.
• Prevent wastage and identify process improvements to contain and reduce costs.
• 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.
• 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.

You Will Be an Ideal Candidate If You Have

• Mathematical/Analytical/Actuarial Science B.Sc. degree or B. Com degree with:
• 5 – 8 years' experience in an analytical and/or modelling position
• 3 years in a management role leading a team (Non-Negotiable)
• Data science and big data knowledge preferable
• Pricing experience, added advantage
• Good communication skills
• Quantitative and analytical skills
• Financial modelling skills
• SAS, Python, SQL, Teradata, PowerBI programming preferable
• Good interpretation skills

You will have access to

• Opportunities to network and collaborate
• A challenging working environment
• Opportunities to innovate

We can be a match if you are / have

• Analytical
• Adaptable and curious
• Thrive in a collaborative environment
• Conceptual and Big Picture Thinking
• Strategic Thinking

Apply now if you are interested in taking the next step. We look forward to engaging with you
All appointments will be made in line with FirstRand Group's Employment Equity plan. The bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfil this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.

*Job Details
Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below. *
25/09/25

All appointments will be made in line with FirstRand Group's Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.

At
X, bigly labs
, we're Dis-Chem's high-performance innovation hub, where bold ideas meet data, design, and radical customer focus. Our mission is simple:
power the future of healthcare
by lowering costs, improving outcomes, and unlocking new possibilities. We're driven by one big question:
How do we use data + technology today to create healthier lives tomorrow?
Here, we don't just imagine the future,
we build it
. From cutting-edge digital solutions to smarter, patient-focused experiences, we're reimagining health tech to make breakthroughs possible.

Welcome to
X, bigly labs.
This is healthcare, reimagined.

From retail and pharmacy to clinics, insurance and beyond, we're applying machine learning and smart systems to reimagine healthcare pathways and create personalised experiences at scale. Here, your work doesn't sit in a notebook or on a whiteboard. It becomes real. It shapes decisions. It improves lives. And we do it all the Bigly way, questioning, challenging, and building audaciously, together.

The
Data Science Lead
will spearhead the development and deployment of advanced analytics and machine learning solutions across the organisation. This role is responsible for driving data-driven decision-making, leading a team of data scientists, and ensuring scalable, secure, and efficient implementation of models using cloud-native technologies.

WHAT WE'RE LOOKING FOR?
Minimum

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 8+ years of experience in data science, with at least 3 years in a leadership or senior technical role.
• Proven experience in designing, developing, and deploying machine learning models in production environments.
• Extensive hands-on experience with cloud-native tools and platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI Platform).
• Strong proficiency in Python, R, SQL, and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow).
• Solid understanding of data engineering principles and cloud data architectures.
• Excellent communication and stakeholder management skills.

Advantageous

• Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Experience in developing and deploying pre built models (e.g. Large Language Models).
• Experience in healthcare, retail, or insurance data ecosystems.

WHAT YOU WILL BE DOING?

• Model Development & Deployment
• Accelerate Analytics and AI Adoption
• Collaboration & Stakeholder Engagement
• Innovation & Research
• Team Leadership and Capability Building

WHO YOU ARE?

• Analytical mindset with attention to detail.
• Comfortable working in fast-paced, evolving environments.
• Willingness to pivot strategies based on feedback and results.
• Passion for exploring new technologies and methodologies.
• Encourages experimentation and creative thinking.
• Commitment to responsible AI practices and data privacy and upholds transparency and fairness in model development and deployment.

Our values aren't just ideals, they're the through-lines in how we think, build, and make decisions that impact real lives. From bold experimentation in digital solutions to platforms built on integrity, we're shaping a culture designed for
progress that lasts
. It's a culture that
designs for the future
, asks better questions, and answers them with care, urgency, and systems that scale.

Think you've got the energy, the curiosity, and the guts? Stay close
b
igly things are ahead.

Job Description

The Pricing Manager will lead strategic pricing for Transact interest and facility fees, driving revenue and profitability through data‑driven decision making. This role implements Analytics standards across assigned business units and converts data into monetisation opportunities by developing and deploying advanced mathematical models and commercial frameworks. The Pricing Manager uncovers hidden patterns and associations in customer and transaction data to shape pricing strategy, optimise channel design, and predict client behavior for improved product performance and customer outcomes.

• Ensure adoption and localization of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Establish goals and strategies for area of accountability in collaboration with senior data analytics management.
• Ensure 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 drive resolution of Privacy and Protection Audit.
• Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Provide and use data and analytic insights to improve customer experience through a better understanding of the customers context to identify monetization opportunities.
• Manage analytics team in the creation of high-quality analyses for all functions of the business, across area of accountability.
• Create tactical plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Drive team performance of analytics solutions; drive and enhance data systems and streamline business processes to impact overall business results while keeping costs in check.
• Analyse available data to identify information commercialization opportunities that have not been explored to address business needs and revenue options.
• Ensure analytics productionization 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 Data and information management function and forums for resolution.
• Oversee the appropriate manipulation and analysis of data for to meet needs of the business for the purpose of future work and to ensure high information-quality and reliability across the business.
• Integrate analytics into operational processes to improve efficiency and client experience.
• Ensure development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques.
• Manage overall project dependencies management and long-term prioritization of the business's overall analytical needs and opportunities.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Define the business questions for Business unit that need be answered; define appropriate analytics models in addition to identifying and readying relevant data sources for analysis.
• Address business problems and opportunities through robust underlying analytics.
• Translate business requirements into tangible solutions or models utilizing own understanding of business value and interrelated nature of projects, models and processes.
• Ensure accurate development and application of 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.
• Provide requirements to Business Information.
• Management Function as Supplier or Owner of Data to ensure data is prepared for consumption as an organizational asset.
• Create team tactical plans for achievement of outputs or deliverables in collaboration with Technology stakeholders to ensure the effective implementation of analytical solutions and models to support business requirements.
• Ensure governance and compliance rules are followed in application and implementation of predictive models to enable the business to manage risk.
• Maintain ownership and oversee the implementation of models.
• Monitor output and accuracy of models.
• Ensure the documentation and auditing of relevant models, projects and processes.
• Provide input into business strategies through data analysis that proactively improve efficiency, identify risks, save costs and drive innovation.
• Lead business through efforts that drive business performance and potential by using the existent and new data sources and techniques.
• Enable business unit to understand its own health, finds growth levers, and identify opportunities for optimization.
• Create new data-driven approaches for the purpose of generating business insights through data analytics, information visualization and addressing unanswered business issues in a proactive manner.
• Ensure validation and interpretation of analytical results and creation of reports and presentations for data analytics management, departmental heads/management, and relevant stakeholders.
• Collaborate with numerous departments across the business to assist in the proper use of data that ensure delivery of desired operational results.
• Model and drive a data driven culture that values data as an asset with business value.
• Lead relevant change and communications functions to drive functional maturity.
• Manage people by executing management responsibilities and create an environment that encourages employee growth and performance excellence.
• Prevent wastage and identify process improvements to contain and reduce costs.
• 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.
• Build relationships that allow for the managing of expectations; the sharing of knowledge and diverse insights; and the creation of buy-in.

Additional requirements

• Relevant BSC Degree / Actuarial Science
• Minimum of 5 years' experience in a Data Science role
• Relevant Pricing Experience
• Experience Managing a team

Additional requirementEngage in cross-functional relationships to obtain and to provide work support

Job Details

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.

23/10/25

All appointments will be made in line with FirstRand Group's Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.

Fintech is entering a new phase where operational and commercial excellence has become critical for success. We at MTN believe this is a game changer in terms of our business strategy. We are looking at an incumbent to join us as we build a successful business together.

As part of your portfolio as a
Manager: Data Science
you will:

• Lead the development and implementation of the
  AI and advanced analytics strategy
  , ensuring alignment with MTN Fintech's business objectives.
• Translate business needs into
  AI/ML use cases
  that deliver measurable impact (growth, efficiency, risk mitigation).
• Drive adoption of
  real-time and prescriptive analytics
  , embedding AI into decisioning and product workflows.
• Develop comprehensive implementation plans for data science projects, balancing innovation speed with governance.
• Build frameworks for
  AI readiness assessment
  , ensuring data quality, ethics, and infrastructure alignment.
• Provide analytical insight to shape product, marketing, and risk strategies.
• Foster partnerships with Group Technology and external AI/ML vendors to co-create scalable data solutions.
• Drive delivery of
  end-to-end machine learning pipelines
  from data ingestion to model deployment and lifecycle management.
• Execute
  AI-driven automation
  for fraud detection, customer segmentation, personalization, and pricing optimization.
• Leverage large-scale wallet and transactional data to identify patterns, forecast trends, and optimize risk strategies.
• Apply advanced analytics, including
  deep learning, NLP, computer vision, and graph analytics
  , to solve complex fintech challenges.
• Enable
  MLOps practices
  for model monitoring, retraining, and continuous delivery.
• Collaborate with data engineers to evolve next-generation data platforms (streaming, real-time data lakes).
• Build and scale
  AI-enabled APIs and microservices
  that plug directly into operational and customer-facing platforms.
• Drive
  data democratization
  by developing self-service analytical tools for business teams.
• Explore opportunities for
  data monetization
  through insights-as-a-service and ecosystem partnerships.
• Implement
  Responsible AI principles
  , ensuring fairness, explainability, and transparency across models.

The incumbent
must have
the following:

• Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
• Master's Degree in a Data Science, AI/ML, Statistical or related field (preferred)
• MBA or Masters (advantageous)
• 5 or more years of relevant work experience as a Data Engineer/ Data Scientist
• 4–6 years applied data science; 2+ years owning production AI/ML.
• At least 3 years' experience within a non-traditional FinTech, Banking or Financial Services Sector
• Experience in Data Science and Data Analysis with a specific focus on AI/ ML models within banking, finance and/or telecommunications industry
• Proven delivery of automated decisioning (recommendation/propensity/fraud/forecasting) with quantified business impact.
• Experience in Data Engineering within banking or financial services industry
• Understanding of enterprise-scale systems and technologies used in data infrastructures
• Experience of working in an Agile/DevOps environment
• GitHub or GitLab experience for CI/CD
• Consistent improvement CI/CD applications for collaborations and enhancement to drive develop once and deploy to many mindset through container repositories
• Proficiency in working with Python and its relevant libraries SAS or R / Scala for data clean up and advanced data analytics
• Working knowledge in Hadoop, Apache Spark and related Big Data technologies (MapReduce, PIG, HIVE)
• Demonstrated experience utilizing software tools to query and report data and being software agnostic
• Highly proficient in database management systems like Postgres, Oracle, Mongo, MSSQL
• Experience in data analysis and management, business performance management and/or reporting within the financial sector or banking industry

Ready to make and drive the change with us? Apply now

Closing date: 15 October 2025. Late applications will not be accepted.

Should you not hear from us within 2 weeks of applying, please consider your application unsuccessful.

THE WORK
: Join our dynamic team and embark on a journey where you will be empowered to perform independently and become an SME. Required active participation/contribution in team discussions and contribute in providing solutions to work related problems. Let's create a brighter future together

Use existing research methods and develop new approaches to discover anthropological, ethnographical and sociological insights.

Develop brand tracking systems and convert data into relevant KPI dashboards.

Utilize analytical methodologies, mathematical modeling or optimization techniques to develop intellectual property.

BONUS POINTS IF YOU HAVE:

Advanced proficiency in Generative Design

Advanced proficiency in Machine Learning

HERE'S WHAT YOU WILL NEED:
Expert proficiency in Data Science.

Advanced proficiency in Data Analytics.

A minimum of 1 year of experience in relevant related skills.

Bachelor's Degree in relevant field of studies

BONUS POINTS IF YOU HAVE:
Advanced proficiency in Generative Design

Advanced proficiency in Machine Learning

• Application Deadline: 29 October 2025
• Job Location: Stellenbosch, Western Cape
• Job Title: COO (Data Science)
• Education Level: Bachelors Degree
• Job Level: Management
• Minimum Experience: Years

Duties and Responsibilities:

• Working as part of a high-performance, service-driven group that prides itself on attracting the finest talent, you will find yourself in an environment buzzing with energy, where smart, motivated people collaborate to deliver the best data and technology solutions.
• Will also coordinate the integration of various software systems and collaborate with teams across business units and countries to enable data-driven solutions, improve business processes, and support informed decision-making.

Requirements:

• A degree in a relevant field of study, such as data science, statistics, engineering, or computer science
• At least ten years' experience in relevant fields, including data, analytics, data science, software development, and/or engineering
• Experience in people management and leadership
• Familiarity with CRM software (e.g., HubSpot, Salesforce)
• Advanced understanding of BI and analytics tools (e.g., Tableau, Power BI, Google Analytics)
• Familiarity with data science tools and programming languages (e.g., R, Python, MATLAB, pandas) as well as database languages
• Knowledge of data pipelines and data integrations
• Proven experience in building a data strategy and executing projects, including data science and AI applications
• Experience managing technology projects and product development
• Ability to identify and communicate value-adding, data-driven insights to influence marketing, e-commerce, and broader business decisions
• Strong communication skills across all levels of the organisation
• Willingness to travel internationally
• Availability to work on-site, five days per week
• Knowledge of GDPR and POPIA, with experience implementing compliance measures across business operations
• Experience in e-commerce
• Proactive, creative, and able to take initiative

Job Overview

Business Segment: Business & Commercial Banking

Location: ZA, GP, Johannesburg, 30 Baker Street

Job Type: Full-time

Job Ref ID: A-0001

Date Posted: 10/15/2025

Job Description

To manage the optimal development, deployment, maintenance, and monitoring of high-quality credit risk models throughout the credit life cycle, upholding model governance standards. Apply innovative machine learning techniques, conduct customer-centric data analytics, and contribute to dashboard creation.

Qualifications

Type of Qualification: First Degree

Field of Study: Mathematical Sciences, Risk Management, Analytics, Quantitative Studies

Experience Required

Credit Risk – BCB

Risk & Corporate Affairs

8-10 years

Be able to identify and implement process improvements in model development, deployment, and monitoring workflows within banking environments.

8-10 years

Develop monitoring dashboards and effectively communicating analytical insights and KPIs to stakeholders. Ensuring adherence to model risk management and governance standards, ensuring compliance with regulations and internal governance requirements specific to credit risk models. Strong communication skills, particularly in translating technical modelling concepts into actionable insights for non-technical stakeholders, supporting decision-making.

8-10 years

Experience in credit risk modelling, including development, enhancement, deployment, and monitoring of credit risk models across the credit life cycle and various portfolios. Experienced in the application of machine learning techniques specifically for credit risk modelling, enhancing predictive modelling accuracy. Experience and knowledge of client-centric data analytics, interpreting complex data sets for credit risk assessment, and leveraging alternative data sources.

Additional Information

Behavioural Competencies:

Adopting Practical Approaches

Articulating Information

Developing Expertise

Developing Strategies

Documenting Facts

Interpreting Data

Providing Insights

Technical Competencies:

Collaboration

Creative Problem Solving

Data Analytics & Visualization

Logical Reasoning

Quantitative Analysis

Statistical & Mathematical Analysis

Please note: All our recruitment processes comply with the applicable local laws and regulations.

We will never ask for money or any form of payment as part of our recruitment process. If you experience this, please contact our Fraud line on or

Please note: All our recruitment processes comply with the applicable local laws and regulations. We will never ask for money or any from of payment as part of our recruitment process. If you experience this, please contact our Fraud line on or

Role Overview:

We are looking for a proactive and detail-oriented Maintenance Engineer to support the upkeep, performance, and evolution of our deployed data science solutions. You will play a key role in ensuring that models, data pipelines, and analytic tools remain robust, reliable, and fit-for-purpose post-deployment. This includes monitoring system performance, identifying technical debt, implementing improvements, and coordinating with data scientists, engineers, and business users to address evolving needs.

Key Responsibilities:

● Monitor and Maintain data science solutions in production (e.g., predictive models, dashboards, pipelines, APIs).

● Diagnose and resolve issues related to data drift, model performance degradation, and infrastructure reliability.

● Automate routine checks and health metrics (e.g., forecast accuracy, pipeline run success, data quality indicators).

● Update and patch data science applications and environments (e.g., dependency updates, version control, deprecation fixes).

● Collaborate with Data Scientists and Engineers to refactor, modularize, or improve codebases for maintainability.

Document maintenance processes and changes, ensuring traceability and knowledge sharing.

● Participate in incident response and troubleshooting, including root cause analysis.

● Ensure compliance with security, privacy, and regulatory requirements for maintained systems.

Required Skills and Experience:

● Bachelor's degree in Computer Science, Engineering, Applied Math, or related field.

● 2+ years of experience in a data engineering, MLOps, or software maintenance role.

● Solid understanding of data pipelines, model lifecycle, and productionized data science workflows.

● Proficiency in Python and R, including ability to debug and refactor code.

● Experience with SQL and managing/monitoring large-scale datasets.

● Familiarity with CI/CD tools, version control (e.g., Git), and containerization (e.g., Docker).

● Understanding of ML Ops / DevOps best practices, especially in a cloud-based environment (e.g., AWS, GCP, Azure).

● Strong debugging and troubleshooting skills, especially in production contexts.

● Attention to detail, curiosity, and a mindset geared toward continuous improvement.

Nice to Have:

● Experience with orchestration tools like Airflow, Dagster, or Prefect.

● Experience with monitoring/alerting tools (e.g. Grafana).

● Exposure to machine learning frameworks.

● Understanding of business KPIs and how data science solutions drive impact.

● Ability to communicate technical issues to non-technical stakeholders.

What Success Looks Like:

● Data science systems are running reliably with minimal downtime.

● Proactive maintenance reduces fire-fighting and technical debt.

● Stakeholders trust the outputs and performance of analytics products.

● Data scientists can focus more on innovation than support and fixes.

Candidates who hold a degree in Data Science or Data Engineering from the below Universities will only be considered:

UCT

Wits

Stellenborsch

UP

Regret no Diplomas

Job Type: Full-time

Pay: R35 000,00 - R40 000,00 per month

Ability to commute/relocate:

• Johannesburg, Gauteng: Reliably commute or planning to relocate before starting work (Preferred)

Application Question(s):

• What University did you study at and what degree do you possess?

Work Location: Hybrid remote in Johannesburg, Gauteng