Data Scientist

About Thrive\-AI: Thrive give building constructors, owners, operators and end users the, intelligence, insights and tools to optimise building performance, end user experience, energy use and operating cost. We have three core services: **Thrive Integrate:** We design, install, integrate and commission secure interoperable building automation controls systems that enable building performance to be monitored, analysed and optimised in real time. **Thrive Host:** We collect, store and structure secure, high frequency building performance data in our cloud platform. **Thrive Optimise** : We deliver insights that help clients monitor, control, predict, and optimise building performance using advanced analytics, machine learning, and AI optimisation We are a dynamic team of passionate and straightforward people, inspired by our mission to *‘revolutionise building performance and occupant experience’* . We are building the industry’s most deployable, adaptive and cognitive building performance intelligence hub and operating system. AI is a core part of our product and internal tooling. About the Role: As we expand, we’re looking for an early‑career Data Scientist who’s excited about using leading edge AI techniques to automate data extraction, transformation, and insight generation across diverse data sources. If you’re energised by solving messy data problems and building intelligent tools that scale, you’ll feel right at home. You’ll sit at the intersection of data science, AI engineering, and product innovation. Your work will focus on developing AI‑powered tools that ingest, clean, and transform data from multiple building systems, APIs, and IoT devices. You’ll help us automate what used to be manual, accelerate how quickly we can onboard new customers, and create new capabilities that make our platform smarter over time. This is a hands‑on role with real ownership and the freedom to experiment. **What You’ll Be Doing:** 1. Build AI driven tools that automate data extraction, mapping, and transformation across heterogeneous data sources (IoT sensors, BMS systems, APIs, CSVs, PDFs, and more). 2. Develop and refine ML models for anomaly detection, forecasting, and optimisation of building performance. 3. Apply modern AI techniques — including LLMs, embeddings, and agentic workflows — to streamline data onboarding, metadata generation, and feature engineering. 4. Create pipelines that turn raw, unstructured, or semi structured data into reliable, production ready datasets. 5. Work closely with engineering teams to deploy models and AI tools into our platform at scale. 6. Collaborate with product teams to identify opportunities where AI can reduce friction, improve automation, or unlock new customer value. 7. Build prototypes, internal tools, and proof of concepts that push the boundaries of what’s possible with building data. 8. Continuously explore emerging AI capabilities and assess how they can be applied to our data ecosystem. **What We’re Looking For:** Essential * People who are inspired by our mission and share our beliefs * A degree in a quantitative field or equivalent hands on experience. * Strong Python skills and familiarity with data science and data engineering libraries (Pandas, NumPy, Scikit learn; PyTorch/TensorFlow a plus). * Curiosity and literacy around modern AI/LLM tooling — prompt engineering, vector databases, document extraction, or agent frameworks. * Experience working with real world, messy datasets and transforming them into structured, usable formats. * Understanding of ML fundamentals, especially time series modelling, anomaly detection and AI ethics * Ability to communicate insights clearly and collaborate across teams. * A builder’s mindset — you enjoy prototyping, iterating, and improving systems in a fast moving environment. * Clear communication and ability to work in cross‑functional teams Desirable * Experience with IoT or building related data sources (BMS, HVAC, energy meters, occupancy sensors). * Familiarity with cloud platforms (Azure, AWS, GCP). * Exposure to MLOps tools (MLflow, Airflow, Docker, dbt, etc.). * Interest in sustainability, energy efficiency, or the built environment. What We Offer: * A great team environment * An opportunity to shape the AI and data foundations of a company in scale‑up mode. * Competitive salary and benefits * Structured onboarding and formal mentoring * Clear progression pathways and promotion frameworks * Training budget and support for certifications * Hybrid working * Opportunity to work on AI at scale and with real‑world constraints Please note that BPSS security clearance will be required as part of our recruitment process.