Data Scientist AI Specialist

FirstRand Bank Limited; Gauteng; On-site; ZAR 400 000 - 500 000; Full time

Job summary

A leading bank in South Africa is seeking an AI Practitioner/Data Scientist with expertise in Generative AI and a strong background in data engineering. The ideal candidate should have over 3 years of experience in AI, strong programming skills, and knowledge of cloud platforms. Responsibilities include model development, data collaboration, and deploying AI solutions. This position offers the chance to contribute to innovative AI projects in a dynamic environment. Verify application details before the closing date of 27/01/26.

Qualifications

• 3+ years of experience in AI with a focus on Generative AI (1-2 years).
• Proven experience in data engineering, including ETL processes.
• Hands-on experience with deep learning frameworks.

Responsibilities

• Design, implement, and optimize AI models using Generative AI.
• Collaborate with engineering teams to ensure data quality.
• Deploy AI models in production environments.

Skills

Generative AI

Data Engineering

Python

Machine Learning Algorithms

Communication Skills

Education

Bachelor’s or master’s degree in Computer Science, Data Science, Machine Learning, or a related field

Master's or Ph.D. is advantageous

Tools

TensorFlow

PyTorch

AWS

Docker

Kubernetes

Job description

Description

We are seeking a skilled AI Practitioner/Data Scientist with a deep specialization in Generative AI and a robust background in data. The ideal candidate will have hands‑on experience in designing, developing, and deploying AI models with a focus on generative techniques. This role demands a strong understanding of data engineering principles, making the candidate well equipped to handle the data pipeline challenges inherent in AI and data projects.

GenAI Model Development

• Design, implement, and optimize operational and analytical solutions utilizing Generative AI models.
• Develop and fine‑tune RAG (Retrieval Augmented Generation) frameworks utilizing LLM frameworks such as LangChain, Llama‑Index or other generative frameworks.
• Experiment with new architectures and techniques to push the boundaries of generative AI.

Data Engineering

• Collaborate with data engineering/analyst teams to ensure the availability and quality of data needed for model training and validation.
• Design and maintain scalable data pipelines to handle large volumes of structured and unstructured data.
• Perform ETL tasks with to create optimal data‑warehousing structures (Dimensional modelling) for optimal storage, ease of use and maintainability.
• Integrate data from various sources and ensure its proper storage, transformation, and accessibility.

Deployment and Scaling

• Deploy AI and generative AI models in production environments, ensuring they meet performance, scalability, and reliability requirements.
• Work with DevOps teams to automate the deployment and monitoring of AI models.
• Optimize model inference for performance and cost efficiency in cloud and on‑premises environments.

Collaboration and Communication

• Collaborate with cross‑functional teams, including data scientists, engineers, product managers, and business stakeholders, to align AI solutions with business objectives.
• Communicate complex AI concepts and findings to non‑technical stakeholders.

Continuous Learning and Innovation

• Stay up to date with the latest advancements in Generative AI and data engineering.
• Participate in conferences, workshops, and other professional development opportunities.
• Contribute to research publications and patent filings in the field of Generative AI.

Requirements

• 3+ years of experience in AI, with a focus on Generative AI (1‑2 years).
• Proven experience in data engineering, including data pipeline development, ETL processes, and database management.
• Hands‑on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and Generative AI frameworks.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerisation technologies (e.g., Docker, Kubernetes).

Technical Skills

• Proficiency in programming languages such as Python, SQL, and familiarity with data manipulation libraries (e.g., Pandas, NumPy).
• Strong knowledge of machine learning algorithms, neural networks, and generative models.
• Experience with data storage solutions (e.g., Hadoop, Spark, Vector databases).
• Knowledge of MLOps practices, including model versioning, monitoring, and retraining.

Soft Skills

• A proactive attitude with a passion for learning and innovation.
• Excellent communication and teamwork abilities.
• Strong problem‑solving and analytical skills.

Preferred Qualifications and Certification

• Bachelor’s or master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• Master's or Ph.D. is advantageous.
• Any of the following certifications are highly advised: AWS Certified AI Practitioner, AWS Certified Machine Learning, GCP Professional Machine Learning Engineer, GCP Associate Cloud Engineer, Microsoft Azure AI engineer, Microsoft Azure Data Science.

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below. Closing date: 27/01/26

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.