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.