Data Scientist (Generative AI)

Be part of our team of Data Specialists and embark on a career of the future! The Data Scientist will be responsible for designing, developing, and deploying Generative AI models to drive innovation and business value.

The ideal candidate will work closely with cross-functional teams to enhance AI-driven solutions, optimise data pipelines, and contribute to the organisation's AI strategy.

Key Responsibilities:

1. Develop and deploy Generative AI models for real-world applications, including text, image, and video generation.
2. Implement and fine-tune large language models (LLMs) and deep learning architectures.
3. Work with structured and unstructured data to develop innovative AI-driven solutions.
4. Collaborate with data engineers and software developers to integrate AI models into production environments.
5. Optimise and scale AI models to improve performance, efficiency, and cost-effectiveness.
6. Conduct research on emerging AI technologies and stay updated with advancements in Generative AI.
7. Ensure compliance with data governance, security, and ethical AI guidelines.
8. Present insights and recommendations to business stakeholders through data storytelling and visualisations.

Requirements:

1. Experience: Minimum 5+ years of experience in Data Science, AI / ML, or a related field.
2. Generative AI Expertise: Hands-on experience with LLMs, GANs, VAEs, and transformer-based architectures.
3. Programming Skills: Proficiency in Python, TensorFlow, PyTorch, and OpenAI API.
4. Data Engineering & Analytics: Strong understanding of SQL, Spark, and big data processing frameworks.
5. Cloud & DevOps: Experience with AWS, Azure, or GCP for AI / ML model deployment.
6. MLOps & Model Deployment: Experience with Docker, Kubernetes, and CI / CD pipelines for AI applications.
7. Statistical & Mathematical Skills: Solid foundation in probability, statistics, and linear algebra for AI model development.
8. Business Acumen: Ability to align AI solutions with business objectives and drive actionable insights.

Preferred Skills & Experience:

1. Experience in NLP, Computer Vision, or Speech AI.
2. Knowledge of Reinforcement Learning (RL) and Self-Supervised Learning (SSL).
3. Understanding of data privacy and AI ethics frameworks.
4. Experience with AutoML tools and AI model interpretability techniques.
5. Published research or contributions to open-source AI projects is a plus.

Strong analytical and problem-solving skills. Ability to work independently and collaboratively in a dynamic environment. Effective communication skills, with the ability to explain complex AI concepts to non-technical stakeholders. Passion for innovation and continuous learning in AI / ML.

Skills: Data Science, Artificial Intelligence, Machine Learning, Python, SQL