Data Scientist ( AI Specialist )

FNB South Africa; Bellville; On-site; ZAR 60 000 - 100 000; Full time

Job summary

Join a forward-thinking organization as an AI Practitioner/Data Scientist, where you will leverage your expertise in Generative AI and data engineering to design and deploy innovative AI models. This role involves collaborating with cross-functional teams to ensure data quality, optimizing data pipelines, and communicating complex AI concepts to stakeholders. You will be at the forefront of AI innovation, contributing to research and staying updated with the latest advancements. If you are passionate about AI and eager to make a significant impact, this opportunity is perfect for you.

Qualifications

• 3+ years of experience in AI, with 1-2 years in Generative AI.
• Proven data engineering experience including ETL processes.
• Hands-on with deep learning frameworks and cloud platforms.

Responsibilities

• Design and optimize solutions using Generative AI models.
• Collaborate with data teams for data quality and availability.
• Deploy AI models in production, ensuring performance.

Skills

Python

SQL

Data Engineering

Generative AI

Deep Learning

Machine Learning

Problem-Solving

Communication

Education

Bachelor’s in Computer Science

Master’s in Data Science

Ph.D. in related fields

Tools

TensorFlow

PyTorch

AWS

GCP

Azure

Docker

Kubernetes

Hadoop

Spark

Job description

We are seeking a skilled AI Practitioner/Data Scientist with deep expertise in Generative AI and a strong background in data management. The ideal candidate will have hands-on experience in designing, developing, and deploying AI models, especially generative techniques. A solid understanding of data engineering principles is essential to handle data pipeline challenges in AI projects.

GenAI Model Development

1. Design, implement, and optimize solutions using Generative AI models.
2. Develop and fine-tune RAG (Retrieval Augmented Generation) frameworks using LLM frameworks such as LangChain and Llama-Index.
3. Experiment with new architectures to advance generative AI capabilities.

Data Engineering

1. Collaborate with data teams to ensure data quality and availability for training and validation.
2. Design and maintain scalable data pipelines for large structured and unstructured data sets.
3. Perform ETL tasks and create efficient data-warehousing structures.
4. Integrate data from multiple sources, ensuring proper storage and accessibility.

Deployment and Scaling

1. Deploy AI models in production, ensuring performance and scalability.
2. Work with DevOps teams to automate deployment and monitoring.
3. Optimize inference for performance and cost-efficiency in cloud and on-prem environments.

Collaboration and Communication

1. Work with cross-functional teams to align AI solutions with business goals.
2. Communicate complex AI concepts to non-technical stakeholders.

Continuous Learning and Innovation

1. Stay updated with the latest in Generative AI and data engineering.
2. Participate in professional development activities.
3. Contribute to research publications and patents in Generative AI.

Requirements

1. At least 3 years of experience in AI, with 1-2 years focused on Generative AI.
2. Proven experience in data engineering, including pipeline development and ETL processes.
3. Hands-on experience with deep learning frameworks like TensorFlow and PyTorch, and Generative AI frameworks.
4. Experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).

Technical Skills

1. Proficiency in Python, SQL, and data libraries such as Pandas and NumPy.
2. Strong knowledge of machine learning algorithms and neural networks.
3. Experience with data storage solutions like Hadoop, Spark, and vector databases.
4. Knowledge of MLOps practices including model versioning, monitoring, and retraining.

Soft Skills

1. Proactive attitude with a passion for learning.
2. Excellent communication and teamwork skills.
3. Strong problem-solving and analytical abilities.

Preferred Qualifications and Certifications

1. Bachelor’s or Master’s in Computer Science, Data Science, or related fields; Ph.D. is a plus.
2. Certifications such as AWS Certified AI Practitioner, GCP Professional ML Engineer, Microsoft Azure AI Engineer, among others.

Note: Applications are due by 09/05/25. The organization supports diversity and inclusion initiatives, including the recruitment of individuals with disabilities. Candidates may disclose disability status voluntarily; this information will be kept confidential.