asBuilt
Data Science Manager
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Data Science Manager
Location: London, UK (On Site)
Employment Type: Full-time
Company: asBuilt IQ
Reporting to: Head of Data Science
About asBuilt IQ
asBuilt IQ is a technology company transforming how infrastructure and construction organisations plan, deliver and manage complex operations.
Our product platform brings together AI, data science, geospatial intelligence, computer vision, optimisation and digital engineering to help customers make better operational decisions. Our solutions address real-world infrastructure challenges including intelligent scheduling, short-term planning, asset intelligence, computer vision, predictive analytics, visualisation and operational performance.
We operate in a fast-moving technology environment, working closely with major infrastructure organisations to take AI and Data Science solutions from concept and experimentation through to production deployment and measurable operational value.
The Role
We are looking for a Data Science Manager to lead the day-to-day operation and delivery of our Data Science function. This is a hands-on player-coach role. You will manage and develop the Data Science team while also personally contributing to the design, development and delivery of Data Science/AI solutions. You should be comfortable writing Python and developing models, reviewing another Data Scientist’s approach, managing delivery priorities, and explaining results to a customer. You will remain actively involved in technical delivery, particularly on complex, high-value or early-stage problems where hands-on Data Science expertise is required.
As part of a growing technology company, you will need to be comfortable working with ambiguity, moving quickly from problem definition to prototype, and taking ownership of delivering solutions into production.
Key Responsibilities
Hands-on Data Science, AI & Technical Delivery
You will remain an active practitioner and personally contribute to Data Science delivery. Responsibilities include:
- Conduct exploratory data analysis and identify patterns, relationships and opportunities within complex operational datasets.
- Build, test and improve machine-learning, statistical and optimisation models.
- Write high-quality Python and develop analytical and modelling pipelines.
- Prototype new Data Science and AI capabilities.
- Develop optimisation approaches for scheduling, routing, resource allocation and operational decision-making.
- Contribute directly to computer vision, predictive analytics and AI initiatives.
- Evaluate model performance and identify opportunities for improvement.
- Diagnose and resolve model, data and production-performance issues.
- Support the productionisation and deployment of Data Science solutions alongside Engineering.
- Analyse production and customer data to understand whether solutions are delivering the intended operational outcomes.
- Produce analyses, visualisations and evidence that communicate model performance and business value.
- Step directly into critical project delivery when additional technical capability is required.
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Data Science Leadership & Team Management
- Lead the day-to-day operation of the Data Science team.
- Manage priorities, workload, resources and delivery commitments.
- Provide technical direction and mentoring to Data Scientists.
- Review modelling approaches, code, experiments and analytical outputs.
- Establish clear technical ownership across projects and products.
- Ensure appropriate standards for experimentation, validation, documentation and productionisation.
- Support recruitment, onboarding and professional development of Data Science talent.
- Identify technical blockers early and actively help the team resolve them.
- Create an environment where Data Scientists can experiment while remaining accountable for delivering production outcomes.
Product Development
- Work closely with Product and Engineering to turn operational problems into scalable Data Science capabilities.
- Contribute to the AI and Data Science roadmap across the VAULT platform.
- Translate product requirements into technical Data Science requirements.
- Rapidly prototype new capabilities to validate feasibility and customer value.
- Help transition successful experiments and proof-of-concepts into robust production solutions.
- Identify opportunities to create reusable models, algorithms and Data Science/AI services across multiple customers.
- Balance customer-specific requirements against the need to build scalable product capabilities.
- Evaluate emerging AI technologies and determine where they can create meaningful product value.
Customer & Project Delivery
- Act as a senior Data Science representative in customer workshops and delivery discussions.
- Work directly with customers to understand operational processes, constraints, datasets and desired outcomes.
- Translate complex operational problems into structured Data Science problems.
- Perform analysis required to answer customer questions and validate proposed solutions.
- Present analytical findings, model behaviour and recommendations to technical and non-technical audiences.
- Support pilots, proof-of-concepts and production implementations.
- Investigate issues identified during customer testing and production use.
- Proactively identify delivery risks, data-quality issues and technical dependencies.
- Ensure Data Science work is connected to measurable operational and commercial outcomes.
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What We’re Looking For
- Approximately 6+ years of professional experience in Data Science, Machine Learning, AI, Operations Research or a related discipline.
- Strong hands-on Data Science/AI capability.
- Advanced Python skills and experience working directly with complex datasets.
- Strong experience developing machine-learning, statistical or optimisation models.
- Experience taking models from experimentation through to production use.
- Previous experience leading Data Scientists, ML Engineers or technical project teams.
- Ability to review and challenge technical approaches developed by other Data Scientists.
- Strong understanding of model validation, experimentation and performance evaluation.
- Ability to structure ambiguous business and operational problems into analytical solutions.
- Strong stakeholder management and communication skills.
- Experience working directly with customers, product teams or operational stakeholders.
- Ability to switch effectively between hands-on technical work, team leadership and customer delivery.
- Comfortable operating with significant autonomy and accountability.
Desirable Experience
Experience in one or more of the following would be particularly valuable:
- Scheduling, routing or resource optimisation
- Computer vision
- Geospatial analytics
- Forecasting and predictive modelling
- Generative AI, LLMs, RAG or agentic AI
- Azure or other cloud platforms
- MLOps and production model monitoring
- Infrastructure, highways, construction, transport, utilities or asset management.
- Digital twins or spatial/engineering technology
- B2B SaaS or enterprise technology environments
- Start Up environment
Direct infrastructure experience is advantageous but not essential. We are particularly interested in candidates who have successfully applied Data Science to complex operational problems.
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