AI & Data Security

Job Summary:The AI & Data Security Specialist is responsible for supporting data management, data security, and artificial intelligence initiatives by ensuring the secure collection, processing, integration, and utilization of organizational data. The role contributes to maintaining data quality and governance, developing data-driven and AI use cases, and supporting the secure implementation and evaluation of AI and Machine Learning solutions.Key Responsibilities:Collect, clean, transform, integrate, and prepare data from internal and external sources while ensuring appropriate data security controls.Support ETL/ELT processes and data integration into data warehouses and analytical platforms.Manage operational, master, reference, and metadata to ensure data accuracy, consistency, integrity, and availability.Monitor data quality and identify errors, inconsistencies, and potential data security risks.Implement and support data governance, data classification, data sharing, and data protection policies and procedures.Ensure compliance with applicable data protection, cybersecurity, and regulatory requirements.Support the development of secure dashboards, analytical reports, and data visualizations.Analyze data to identify trends, patterns, opportunities, and potential risks and provide actionable insights.Support the identification and analysis of AI and data use cases that deliver measurable business value.Prepare datasets for AI and Machine Learning model training and testing while ensuring data security and appropriate access controls.Support the development and evaluation of predictive and classification models using relevant performance metrics such as accuracy, precision, and recall.Required Qualifications:Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Cybersecurity, Information Security, Information Technology, or a related field.Experience in Data, AI/ML, Data Security, Cybersecurity, or a related field.Knowledge of data security, data governance, data protection, and data quality principles.Knowledge of ETL/ELT, data integration, and data warehouse concepts.Understanding of AI/ML concepts, predictive analytics, and model evaluation.Preferred Skills:SQL and database technologies.Python.Power BI or Tableau.ETL/ELT and data integration tools.