Data Scientist

Senior Data Scientist

We're looking for an exceptional Senior Data Scientist with AI expertise to join our Analysis team and help shape the intelligent backbone of our 3D design and GIS product ecosystem. You'll play a key role in developing machine learning models, predictive systems, and AI-driven analytics that power and enhance our data pipeline infrastructure and product intelligence.

This is a hands-on role focused on applying AI techniques to both geospatial and non-geospatial data, 3D workflows, and internal datasets to drive automation, insights, and new product capabilities. We present an opportunity to contribute to novel research into developing spatial intelligence models, as well as the practical application of existing cutting edge techniques.

Work within the Analysis Team to develop and deploy ML (including LLM) models that enhance our 3D design/GIS platforms and internal tooling.
Collaborate with cross-functional teams including Product, Engineering, and Data Engineering to translate business challenges into scalable ML solutions.
Collaborate with external AI specialists to deliver larger-scale projects.
Explore, clean, and transform large datasets for training, validation, and inference, including geospatial and 3D data types.
Design, test, and deploy predictive models and recommendation systems into production environments. Identify and develop opportunities for AI-powered automation and decision-making tools.
Contribute to the architecture of intelligent data pipelines that support both internal operations and customer-facing features.
Continuously evaluate model performance and apply strategies for tuning, retraining, or improvement.
Participate in product and project planning to help prioritise AI-driven initiatives.
Mentor team members by sharing ML best practices and helping to build a culture of technical excellence.
Stay current with emerging ML techniques and technologies, and evaluate their potential for our use cases.
Support team delivery and maintain clear communication on changing goals, plans, or requirements.
What you'll need to succeed:
Hands-on experience working with LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments.
Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools.
A solid understanding of tokenisation, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) pipelines.
Experience designing and evaluating LLM-powered systems such as chatbots, summarisation tools, content generation workflows, or intelligent data extraction pipelines.
Deep understanding of NLP fundamentals: text preprocessing, language modelling, and semantic similarity.
Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar.
Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow).
Familiarity with cloud-based AI tools and infrastructure, especially within the AWS ecosystem (SageMaker, Lambda, etc.).
Strong understanding of data structures, algorithms, and statistical analysis.
Experience working with ETL pipelines and structured/unstructured data.
Solid grasp of software engineering principles, version control systems (Git), and Agile methodologies.
Ability to break down complex data challenges into clear, manageable tasks.
Clear communicator and problem solver with a positive, proactive attitude.
Highly self-motivated with a passion for learning and growing in the AI/ML domain.
Comfortable working both collaboratively and independently in a dynamic, fast-paced environment.
Must be available to attend quarterly company meetings in person.
Be human and ready to have fun.
Nice to haves:
Experience applying AI to 3D or GIS domains.
Familiarity with game engines (Unity, Unreal) and 3D modelling software (Revit, AutoCAD, 3ds Max, Blender).
Experience with AWS data systems such as Lake Formation, RDS, DynamoDB, ElastiCache.
Exposure to spatial or temporal modelling, simulation, or generative AI models. Experience with containerised deployment (Docker) and AIOps practices.

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