Head of Construction Data and A.I.

What we are recruiting for:

As the Head of Construction Data and AI, you will bridge the gap between site-level delivery and modern data engineering. This is a strategic role requiring deep domain expertise in the

construction lifecycle - understanding why schedules slip, identifying discrepancies in commercial reporting, and navigating the complexities of procurement and cost planning.

You will be the hands-on architect of our data roadmap, moving beyond high-level strategy to

personally prototype models and drive data evolution across key business domains such as: Design, Commercial, Planning, Operations and SHEQ . While specialist partners build the core infrastructure, you will be actively involved in the technical detail - defining logic, wrangling complex datasets, and validating outputs to ensure they solve real-world site challenges. You are a player-coach who leads by example, mentoring analysts while staying deeply embedded in the "how" of our technical delivery.

Key Responsibilities

Practical AI & Solution Development

• Hands-on Delivery: Lead the end-to-end development of data and AI solutions across the key business domains, ensuring every model, tool is built for field reality, not theoretical use cases.
• Applied Innovation: Define and drive the AI use-case roadmap across three core capability areas:
• Machine Learning & Predictive Modelling - designing, training, and deploying models for construction-specific problems (cost forecasting, programme risk, productivity analysis, defect prediction) using production-grade frameworks and current best-in-class approaches.
• Generative AI & Language - developing agentic workflows, document processing pipelines (OCR, contract analysis, specification extraction), and RAG systems that make the organisation's unstructured knowledge searchable and actionable. Computer Vision - applying image and video analysis to site progress monitoring, quality inspection, safety compliance, and asset condition assessment.

Data Architecture & Integration

• Workflow Mapping: Evaluate and translate complex construction dataflows into technical requirements, ensuring data models for programme, cost, design, procurement, sheq accurately reflect how work moves through a construction project. Strategic Integration: Lead the technical specification and ingestion ETL/ELT of data from corporate systems.

Advanced Analytics & Modeling

• Predictive Insights: Develop and refine diagnostic models for program risk, cost overruns, and productivity using diverse datasets, including structured records, site imagery, and IoT feeds. Validation & Testing: Own the experimental lifecycle - personally defining how we prototype, measure, and prove the value of data initiatives before scaling them across the business.

Technical Governance & Safety

• Regulatory Rigor: Establish robust governance and model validation practices that meet the high standards of a regulated environment, specifically regarding the Building Safety Act and safety-critical decision-making. Technical Quality Control: Direct external technology partners to ensure platform builds reflect complex construction logic rather than generic enterprise patterns.

Leadership & Influence

• Cross-Functional Leadership: Drive organisational technical adoption across project teams and business units through influence and expertise rather than formal hierarchy. You will lead by building consensus, demonstrating practical value, and establishing yourself as a trusted advisor to both site and executive leadership Mentorship: Act as a "player-coach" for internal analysts, raising the bar for technical excellence and data literacy across the organisation.

Credentials

Degree in a relevant discipline (Computer Science, Data Science, Engineering, Construction Management, or equivalent practical experience). Evidence of continued professional development in data science, AI/ML, or related fields

Essential Skills, knowledge, experience, behaviours (Not limited too)

Skills

• Advanced Python proficiency with hands-on production use of ML/DL frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent)
• Ability to design, build, and deploy GenAI solutions including agentic workflows, RAG architectures, and document processing/OCR pipelines
• Data architecture design - structuring, modelling, and integrating data from multiple disconnected systems into coherent, queryable datasets
• Data visualisation and BI delivery using Power BI or equivalent, producing outputs construction teams will actually use
• Technical specification writing - ability to produce clear, detailed requirements for external technology delivery partners
• Translating complex technical concepts into plain language for non-technical stakeholders at all levels

Knowledge

• Deep understanding of construction project lifecycles – must have, commercial processes, and how programme, cost, procurement, design, quality, and safety functions interact
• Working knowledge of NEC and JCT contract forms and how contractual mechanisms generate data requirements Familiarity with UK construction regulatory frameworks - Building Safety Act, CDM Regulations, golden thread principles
• Current ML/AI landscape including supervised/unsupervised learning, NLP, computer vision, and generative AI
• MLOps principles - experiment tracking, model versioning, drift detection, CI/CD for ML pipelines, automated retraining
• Understanding of both commercial AI APIs (OpenAI, Anthropic) and open-weight models (Llama, Mistral, DeepSeek) and the trade-offs between them regarding data sovereignty, cost, and offline capability

Experience

• Significant experience (10+ years) working in or directly with the construction industry in a data, analytics, or technology-focused capacity
• Proven track record of delivering AI/ML solutions end-to-end - from problem definition through to production deployment and ongoing monitoring - not just experimentation
• Experience designing data integrations across multiple business systems where no single source of truth exists
• Leading or directing external technology delivery partners, maintaining oversight of scope, quality, and architectural decisions
• Mentoring and developing data professionals, building team capability rather than creating dependency
• Presenting data and AI strategy to senior leadership and translating outcomes into business impact

Behaviours

• Construction-first mindset - instinctively frames every technical solution around how it will be used on site and in project teams
• Pragmatic delivery focus - knows when "good enough now" beats "perfect in six months" and acts accordingly
• Intellectually honest - willing to say when an AI approach won't work, when data quality isn't sufficient, or when a simpler solution is the right answer
• Resilient under ambiguity - comfortable operating without a fully defined roadmap, making decisions with incomplete information, and adjusting course as the business evolves
• Collaborative without being passive - builds strong working relationships with key stakeholders Business, Project Leads, Heads of Departments, IT, Clients…
• Proactive communicator - doesn't wait to be asked, surfaces risks and opportunities early, and keeps stakeholders informed without being prompted
• Calm and effective under pressure, particularly during peak project periods or when responding to urgent requests

Belong at Bovis

Bovis is committed to being a diverse and inclusive employer of choice by engaging, enabling and empowering our people. All qualified applicants will receive consideration for employment, and we are happy to consider flexible working arrangements. Inclusion sets us all up for success and we particularly encourage applications from currently under-represented groups in our industry including those who self-identify as women, black, Asian, minority ethnic, lesbian, gay, bisexual, transgender and/ or disabled.