AI Specialist

The AI Specialist will be a hands-on technical expert responsible for designing, developing, implementing, and maintaining artificial intelligence and machine learning models to solve complex business problems within NADEC. This role involves working closely with data scientists, data engineers, and business stakeholders to identify opportunities for AI, develop robust solutions, and contribute to the continuous improvement of NADEC's operational efficiency, product innovation, and customer experience through AI.

Core Accountabilities:

AI/ML Model Development & Implementation: Design, develop, train, and deploy machine learning models (e.g., for predictive o analytics, natural language processing, computer vision, anomaly detection, o recommendation systems).

Perform data collection, preprocessing, feature engineering, and validation for o AI/ML models. Write production-quality code for AI/ML solutions and integrate them into o existing systems and workflows. o Optimize models for performance, scalability, and accuracy.

Research & Innovation: o Stay current with the latest advancements, techniques, and tools in AI, machine o learning, and deep learning.

o Evaluate and experiment with new AI technologies and methodologies to o assess their potential value for NADEC.

Contribute to the development of innovative AI-driven solutions to address o specific business needs in areas like agriculture, manufacturing, supply chain, o and sales & marketing.

Data Analysis & Interpretation:

o Collaborate with data analysts and business users to understand data sources o and requirements for AI projects.

o Analyze large datasets to identify patterns, insights, and opportunities for AI o application. o Clearly communicate complex AI concepts and model results to both technical o and nontechnical audiences.

Model Monitoring & Maintenance:

Develop and implement strategies for monitoring the performance of deployed o AI models. o Perform ongoing maintenance, retraining, and fine-tuning of models to ensure o continued accuracy and relevance.

o Troubleshoot and resolve issues related to AI model performance or o deployment.

o Collaboration & Documentation:

Work collaboratively in an agile environment with cross-functional teams o including data engineers, software developers, and business stakeholders. o Document AI models, methodologies, processes, and results thoroughly.

o Participate in code reviews and knowledge-sharing sessions Public

Ethical AI:

Ensure that AI solutions are developed and deployed responsibly, considering o fairness, transparency, and ethical implications