Sr Expert AI & Data Science

Key ResponsibilitiesAct as a senior technical advisor on AI, machine learning, data science, analytics, and AI-enabled data architecture, providing recommendations to management and project teams.Support SHIB Data & AI workstreams, including review of AI platform, model lifecycle, vector/retrieval, knowledge-layer, data architecture, and related vendor deliverables.Assess emerging AI technologies, architecture patterns, industry practices, and market trends, and translate them into practical recommendations for Sahati.Lead and perform advanced analytics, data science studies, proof-of-concepts, exploratory analysis, statistical modeling, and business problem solving across healthcare and insurance use cases.Contribute to AI use-case design and prioritization, including predictive analytics, anomaly detection, intelligent automation, NLP/LLM use cases, decision support, and advanced reporting.Work with data engineering and platform teams on data readiness, analytical datasets, data pipelines, structured/unstructured data, FHIR/JSON data, and integration requirements needed for analytics and AI.Review data quality, completeness, consistency, and usability issues; support practical remediation and readiness activities for analytics, reporting, and AI workloads.Support executive and regulatory reporting, KPI analysis, analytics products, dashboards, ad-hoc studies, and evidence-based decision support where senior technical input is required.Review technical proposals, solution designs, vendor submissions, architecture documents, and implementation approaches; identify risks, gaps, dependencies, and improvement actions.Develop clear technical and executive-ready outputs, including studies, recommendations, presentations, design notes, decision papers, and implementation guidance.Collaborate across data, analytics, governance, technology, product, cybersecurity, GRC, and business teams to deliver integrated end-to-end outcomes.Mentor analysts and technical resources, share good practices, and help raise the maturity of the broader data and AI capability.Required Experience & QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or a related field; advanced degree is preferred.7–8+ years of relevant experience across AI, data science, advanced analytics, data engineering, or enterprise data platforms, with evidence of independent ownership of complex work.Strong hands-on experience with Python and SQL, and practical experience with machine learning / data science libraries and workflows.Solid understanding of modern AI architecture and delivery practices, including model development, evaluation, deployment concepts, MLOps, LLMs, embeddings, RAG/vector retrieval, and model monitoring.Good understanding of data architecture and engineering foundations, including data warehouses/lakehouse concepts, ETL/ELT, APIs, data modeling, metadata, data quality, and structured/unstructured data.Experience translating business problems into analytical or AI solutions and communicating recommendations to both technical and senior non-technical stakeholders.Ability to independently research unfamiliar topics, evaluate options, challenge assumptions, and produce high-quality recommendations under time pressure.Preferred ExperienceHealthcare, health insurance, fintech, government, telecom, or other regulated / national-scale platform experience.Exposure to healthcare interoperability and transaction data such as FHIR/JSON, claims, eligibility, prior authorization, provider/payer data, or similar complex data domains.Experience with enterprise BI and analytics platforms such as Power BI, Oracle BI, Tableau, Qlik, or equivalent, with an understanding of KPI and reporting environments.Experience reviewing vendor architecture, consulting deliverables, technical specifications, or large transformation programs.Familiarity with Saudi data, privacy, AI governance, or regulatory expectations is an advantage.