Senior Specialist Data Science

Role summary

AI application and machine learning delivery

• Design and deploy generative AI and agent solutions on Microsoft Foundry, including model selection, prompt and tool design, RAG and Foundry Agent Service.
• Build Databricks Apps, including interactive tools, RAG assistants, data-entry forms and operational interfaces on Unity Catalog-governed lakehouse data.
• Deliver construction contract review, document intelligence and project risk prediction, integrating with Microsoft 365 and Power Platform.
• Own solutions from requirements through design, build, user acceptance and support handover.
• Develop and deploy forecasting, classification and anomaly-detection models using Databricks, MLflow, Unity Catalog feature tables and Model Serving.
• Run batch and real-time predictions through Power BI, Databricks Apps and business workflows.
• Apply predictive analytics to project controls, cost and commercial, procurement, HSE, plant and workforce data; explain model methods, confidence and limitations.

Evaluation, security and operations

• Evaluate AI accuracy, groundedness, bias and robustness before release; record results and monitor deployed models and agents for drift, failures and answer quality.
• Retrain or roll back when agreed thresholds are breached.
• Implement identity, least-privilege access, secrets management, content safety and PDPL controls for personal and HR data.
• Partner with Data Governance on risk assessments, data residency and registering AI use cases.
• Use CI/CD, automated testing and version control for code, prompts and models.
• Own tracing, monitoring, alerting, incident response and inference and compute costs within agreed budgets.
• Document architectures, data sources, prompts, evaluation results and runbooks for support and handover.

Collaboration and mentoring

• Work with business owners in finance, projects, procurement, HSE and HR to identify valuable use cases and agree success measures.
• Partner with data engineering on feature tables and document and vector pipelines, and with data analysis on Power BI integration.
• Mentor Data Scientists and engineers and help colleagues use approved AI tools safely.
• Explain design choices, trade-offs, risks and model limitations to technical and business audiences.

Required experience and qualifications

• 5+ years of hands-on machine learning, AI or software engineering experience, including 2+ years deploying ML or generative AI solutions in production.
• Shipped generative AI or agent applications on Microsoft Foundry, Azure OpenAI or an equivalent, including RAG, tool calling and systematic evaluation.
• End-to-end machine-learning model development and deployment; Databricks with MLflow is identified as ideal.
• Strong Python and SQL, web application or API experience, and Git-based CI/CD delivery using Azure DevOps or an equivalent.
• Practical security and responsible AI experience, including identity, secrets, content safety, groundedness and bias testing.
• Excellent written and verbal communication across technical and business audiences.
• Within 6 months, hold or achieve AI-103 or Databricks Certified Generative AI Engineer Associate; within 12 months, hold or achieve Databricks Certified Machine Learning Professional or AI-300.
• B.E., B.Tech, B.Sc. or higher in a listed computing, data, AI, IT, engineering or quantitative field; a master's or recognised postgraduate programme in Data Science, AI or Analytics is an advantage.

Preferred qualifications and certifications

• Preferred experience includes Databricks Apps, Mosaic AI Vector Search, Model Serving, Unity Catalog, agent orchestration, multi-agent workflows, MCP servers, construction document intelligence, Copilot Studio, Power Apps, Power Automate and time-series forecasting.
• Multi-entity or multi-country data-residency experience and construction, engineering services, manufacturing, energy or logistics industry experience are preferred.
• Preferred certifications include Databricks Certified Machine Learning Associate, IAPP AIGP, Azure AI Engineer Associate (AI-102, accepted if held), and Azure Data Scientist Associate (DP-100, accepted if held).

Role impact and development