Data Scientist

About the Role As a Data Scientist, you will work closely with our client to solve complex business challenges and develop effective data-driven solutions that support the delivery of quality and affordable housing. You will join a collaborative data science team that partners with business and technology stakeholders to design, develop, and implement high-impact solutions. The role requires strong analytical thinking, technical expertise, and the ability to translate business needs into practical data science applications. Key Responsibilities Contribute as a core team member to strategic and challenging data science projects. Analyse complex business problems and recommend suitable data science approaches, algorithms, and methodologies. Support the end-to-end development, testing, deployment, and maintenance of data science and machine learning solutions. Ensure the accuracy, efficiency, scalability, and integrity of the team’s solutions. Contribute to the improvement of technical workflows, processes, methodologies, and best practices. Review the work of team members to maintain high technical and quality standards. Collaborate closely with IT teams, system project leads, data engineers, and business stakeholders to co-create high-value solutions. Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders. Stay updated on developments in data science, artificial intelligence, machine learning, and Generative AI. Continuously improve technical knowledge and evaluate relevant emerging technologies. Requirements Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline. At least 3 years of relevant hands-on experience in data science, machine learning, or artificial intelligence. Strong analytical and structured problem-solving skills, including experience with approaches such as root cause analysis and MECE frameworks. Good understanding of MLOps principles and experience in end-to-end model development and deployment on cloud platforms such as AWS. Strong knowledge of machine learning, deep learning, statistical modelling, optimisation, and multi-criteria decision analysis. Experience with deep learning architectures and techniques, including transformer models and reinforcement learning. Experience in AI engineering and Generative AI solutions, including: Large Language Models Neural embeddings Retrieval-Augmented Generation LangChain or LangGraph Vector databases Evaluation-driven development Experience with data engineering concepts for data science, including ELT processes, structured data transformation, and database technologies. Strong programming skills in Python, R, SQL, and Shell scripting. Experience with relevant Python machine learning and data science frameworks. Strong communication, presentation, and data visualisation skills. Able to work effectively both independently and within a multidisciplinary team. Strong attention to detail and commitment to delivering high-quality solutions.