Role Overview:

We are seeking a Full Stack Data Scientist with deep expertise in AI, Generative AI (GenAI), and machine learning technologies, especially in the Microsoft Azure ecosystem. This leader will spearhead AI delivery projects, contributing to our growing portfolio across industries such as oil and gas, government, and retail. The ideal candidate will have extensive experience in AI project execution, from data engineering to model deployment, with a strong track record in working with the latest AI models like LLMs (Large Language Models) and RAG (Retrieval-Augmented Generation).

As part of their role, this individual will guide teams, manage complex AI use cases, and deliver end-to-end AI solutions that align with business objectives. The role also requires a blend of strategic foresight, technical depth, and hands-on expertise to successfully integrate AI into operational workflows.

Key Responsibilities:

• AI Project Leadership: Lead the delivery of AI and GenAI projects from inception to deployment, ensuring alignment with business goals, timelines, and resource allocation.
• Technical Delivery Oversight: Design, build, and deploy AI/ML models (including LLMs and RAG models) to solve business challenges, ensuring solutions are optimized for scalability and efficiency.
• Cross-Industry Expertise: Deliver impactful AI solutions tailored to industries such as oil and gas (e.g., predictive maintenance), government (e.g., citizen engagement, process automation), and retail (e.g., customer personalization).
• Data Engineering & Model Training: Oversee data engineering pipelines, ensuring that the right data is accessible, clean, and optimized for machine learning models. Responsible for model training and fine-tuning to meet specific business needs.
• MLOps & Lifecycle Management: Implement robust MLOps practices to ensure models are deployed and managed effectively, including continuous monitoring, retraining, and updates based on performance.
• Presales Support: Engage with clients during the presales phase by presenting technical expertise and crafting tailored AI solutions that address their business needs. Participate in proposals, RFPs, and client workshops.
• AI Advisory & Expertise: Act as a trusted advisor for clients, providing insights and recommendations on how AI can transform their business, improve operational efficiencies, and drive innovation.
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Skills

Skills & Qualifications:

• Proven Experience:
• 5+ years of experience in AI and data science, with hands-on experience in machine learning model development and AI delivery.
• Expertise in full stack AI development, including data engineering, model training, deployment, and ongoing monitoring.
• Track record of delivering complex AI projects, especially in industries such as oil and gas, government, and retail.
• Technical Proficiency:
• Microsoft Azure Expertise: Proven experience building AI solutions within Azure's cloud ecosystem, leveraging Azure AI services such as Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure OpenAI Service, and Azure Cognitive Services.
• GenAI & LLMs: Proficiency in working with the latest Generative AI models, including LLMs (e.g., GPT), RAG (Retrieval-Augmented Generation), and large graphical models. Experience in LLM fine-tuning and prompt engineering is highly valued.
• Data Engineering Skills: Proficiency in data preprocessing, ETL pipelines, and feature engineering to prepare datasets for AI model training. Hands-on experience with tools like Apache Spark or Azure Data Factory is an advantage.
• MLOps & AI Lifecycle Management:
• Solid understanding and implementation of MLOps best practices, including model versioning, continuous integration (CI/CD) for ML models, and automated monitoring of AI systems in production environments.
• Experience in managing the entire AI lifecycle, from development to deployment and post-deployment monitoring, ensuring models stay accurate and reliable.
• Ethical AI & Explainability:
• Deep knowledge of ethical AI principles and a commitment to building AI models that are explainable, fair, and aligned with industry regulations and societal standards.
• Experience working with Explainable AI (XAI) tools to help stakeholders understand the decisions made by AI systems.
• Cross-Functional Collaboration:
• Strong ability to collaborate with diverse teams, including business leaders, data engineers, software developers, and customers, to ensure that AI solutions meet cross-functional goals.
• Excellent communication skills, both technical and non-technical, with the ability to simplify complex AI concepts for business leaders and stakeholders.
• Presales & Client Engagement:
• Experience in presales activities, including crafting proposals, participating in RFPs, and delivering compelling presentations to clients that demonstrate the value of AI solutions.
• Strong business acumen with the ability to align AI solutions with strategic business objectives.
• Continuous Learning & Innovation:
• A passion for staying up to date with the latest advancements in AI, machine learning, and GenAI models.
• Commitment to continuous learning and research in AI trends, ensuring solutions leverage the latest technologies and methodologies.