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.