Data Scientist – Generative AI

SUMMARY:
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POSITION INFO:

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:

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

Requirements:

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

Preferred Skills & Experience:

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

Key Competencies:

• 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.

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