Back to jobsDeep expertise in AI, machine learning, and applied analytics, with experience delivering production-grade AI solutions.
Proven experience building multidisciplinary teams spanning data science, data engineering, and analytics.
Strong experience building and scaling AI and analytics products and platforms in enterprise environments.
Hands-on experience with MLOps practices, including model lifecycle management, automated pipelines, and monitoring.
Experience building or deploying LLM-enabled solutions, such as retrieval-augmented generation (RAG), AI agents, or generative AI applications.
Strong understanding of modern cloud AI ecosystems, particularly Microsoft Azure, Azure AI services, Azure ML, and Databricks.
Experience working with data engineering platforms and scalable data architectures.
Proficiency with modern development workflows including GitHub-based collaboration, CI/CD pipelines, and infrastructure automation.
Strong expertise in predictive modelling, statistical analysis, and machine learning methods including regression, time series, network analysis, and advanced ML algorithms.
Executive communication and stakeholder management skills, with the ability to explain complex technical concepts to non-technical audiences.
Experience applying data science methods to analyse quantitative and qualitative data sets in a market research or academic setting is a plus
