Cobalt Recruitment

About the Company You'll be joining a global leader in real estate services and technology solutions. Known for combining deep market expertise with cutting-edge innovation, this business is committed to modernising how property and investment decisions are made. You'll be part of a collaborative, forward-thinking environment that values creativity, accountability, and growth-where your contributions will directly shape the future of real estate technology. Role Responsibilities Architect, build, and optimise scalable ETL pipelines for diverse datasets. Onboard, document, and curate external datasets for internal use. Perform data validation, forensic analysis, and troubleshooting. Deliver high-quality, maintainable Python code and participate in peer reviews. Collaborate with stakeholders and researchers to support analytics and product development. Integrate data from APIs, S3 buckets, and structured/unstructured sources (JSON, CSV, Excel, PDF, Parquet). Join geospatial datasets with external data sources and apply complex transformations. Define validated data schemas and create clear documentation for partners and teams. Explore and evaluate new data engineering tools and technologies. Role Requirements 5+ years' experience in data engineering, analytics, or related roles. Strong proficiency in Python, with demonstrated experience on large-scale projects. Solid understanding of algorithms, data structures, and relational databases. Experience with test-driven development and Git version control. Portfolio of past work (GitHub contributions, open-source, blogs, or demos). Knowledge of data cleansing, validation, and basic statistics. Background in working with Agile methods and fast iteration cycles. Bachelor's degree in Computer Science, Data Engineering, or related field (or equivalent experience).

About the Company You'll be joining a global leader in commercial real estate services and investment management. Known for combining deep market expertise with innovative technology, the business is committed to modernising how investment decisions are made. You'll be part of a collaborative, forward-thinking environment where your contributions will directly shape the future of real estate technology. Role Responsibilities Design, develop, and implement generative AI and machine learning solutions for commercial real estate. Apply large language models to analyse financial documents and market datasets. Engineer and optimise prompts, as well as evaluate LLM outputs for accuracy and relevance. Build production-ready Python code and integrate models into user-facing applications. Monitor and refine model performance post-deployment, making improvements based on feedback. Collaborate with product and engineering teams to deliver solutions aligned with business goals. Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding of machine learning algorithms and statistical modelling techniques. A degree in Computer Science, Statistics, Machine Learning, Engineering, Physics, or a related quantitative field.