Lead Data Scientist X 2

About the Role
  
Our client is seeking a Lead Data Scientist to join their growing technology team. This role is ideal for someone with experience developing and deploying machine learning solutions to solve complex business challenges, preferably within a software or SaaS environment.
You will work across the full data science lifecycle, from exploratory analysis and experimentation through to production deployment and optimisation. Operating in a fast-paced and collaborative environment, you will partner closely with product, engineering, and data teams to deliver innovative, customer-focused solutions that align with broader business objectives.
The role offers the opportunity to work with a wide range of technologies and approaches, including traditional machine learning techniques such as classification and regression, as well as emerging generative AI applications. The successful candidate will thrive in an environment that values autonomy, creativity, and continuous innovation.
  
Key Responsibilities

• Lead the end-to-end development of machine learning solutions, from problem discovery and experimentation through to production deployment and ongoing optimisation.
• Design and implement predictive and analytical models, including classification, regression, clustering, and other statistical or machine learning techniques to address business challenges.
• Develop and apply generative AI solutions to enhance products, automate processes, and generate valuable insights for users.
• Analyse structured and unstructured data, including natural language content, to identify patterns, extract insights, and support data-driven decision-making.
• Research, evaluate, and prototype new methodologies, tools, and technologies to solve complex problems and drive innovation.
• Collaborate closely with engineering and product teams to integrate, deploy, and scale AI and machine learning capabilities within production environments.

Requirements

• 5+ years’ experience developing and deploying machine learning solutions, ideally within a software, SaaS, or product-focused environment.
• Strong Python programming skills and experience with the core machine learning ecosystem, including libraries such as NumPy, SciPy, scikit-learn, TensorFlow, PyTorch, or similar.
• Solid expertise in Natural Language Processing (NLP), including text representation, classification, information extraction, topic modelling, embeddings, and modern transformer-based approaches.
• Experience applying machine learning techniques across classification, regression, clustering, segmentation, and predictive analytics use cases.
• Familiarity with generative AI technologies and large language model (LLM) applications, including concepts such as retrieval-augmented generation (RAG), prompt engineering, and AI-powered product features.
• Experience researching, evaluating, and implementing new machine learning methodologies to solve complex business problems.
• Proven ability to collaborate effectively with product and engineering teams to deliver production-ready solutions and customer-focused outcomes.
• Comfortable working autonomously in fast-paced environments, navigating ambiguity and changing priorities.
• Experience deploying machine learning solutions in cloud environments and working with modern software delivery practices, including CI/CD pipelines and version control systems.
• Familiarity with containerisation technologies, Linux-based environments, and collaborative development workflows is advantageous.
• Experience with data visualisation or business intelligence tools is beneficial but not essential.