We’re seeking a passionate Data Scientist to own the end-to-end implementation and design of data science applications for various clients. You will join a growing practice and champion and actively contribute to the growth of the discipline, enabling the ongoing growth of the data science capability.
You’ll join a talented team of dynamic and driven professional problem solvers; creative thinkers and solutions builders who thrive on helping clients meet the most exciting digital transformation challenges.
Make a difference and advance your career by helping deliver some of the UK’s most important #tech4good projects, making the world a smarter, safer, greener, and healthier place.
At a certified Great Place to Work® you’ll experience a dynamic and nurturing environment that rewards initiative and flexibility and enjoy a career path tailored to your own aspirations.

ABOUT US

Founded in 1992, we are a successful, growing International digital transformation consultancy. We deliver multi-Queen’s Award for innovation winning platforms and services that support large-scale digital transformation. Our digital, data and technology solutions are used by globally recognised public and private sector brands operating in a variety of sectors including Civil Defence, Healthcare, Sustainable Environment and Land Asset Management, and Digital Democracy.

REQUIREMENTS

• Background in Agile delivery environments, delivering software solutions in controlled increments (e.g., following Scrum, Agile Delivery phases, etc.).
• Experience working with cloud-based solutions and technologies (Google Cloud Platform, AWS, Azure).
• Hands-on knowledge of designing and implementing solutions capable of handling sensitive data (e.g., Personally Identifiable Information).
• Strong knowledge of a programming languages for data science (Python, R, etc.) including best practices using this language to write robust software.
• An understanding of data governance and best practices to ensure data protection.
• Experience planning technical activities and structuring work for a team.
• Being able to provide commercially robust estimates of development activities.
• Experience providing practitioner guidance to junior colleagues and peers.
• Understanding of how to operationalise and deploy a Data Science solution in a live environment.
• A bachelor’s degree in a STEM field.

Desirable skills and experience

• Experience working in a professional services/consultancy environment preferred.
• Experience solving natural language processing problems.
• Experience creating generative AI applications, such as chatbots or RAG retrieval systems.
• Stay up to date with cutting edge of AI, reading research papers, attending conferences, etc.
• Ability to work effectively across multiple teams and projects.
• Ability to explain and simplify complex information to stakeholders, gathering and translating business requirements, anticipating any obstacles to information flow.
• Understanding of different databases (Relational and NoSQL) and optimising queries for effective data manipulation.
• A master’s degree or PhD in a STEM field.

Senior Data Scientists enable the design, development, integration and testing of complex, high quality data science solutions and services to meet user needs, continually improving the application of best practice patterns, methods and tools. This includes:

• Build effective working relationships with client counterparts in your practitioner domain, and those of a partner / 3rd party organisation.
• Own the end-to-end implementation and design of data science models/components, seeking guidance and input from Lead and Principal Data Scientists where necessary.
• Help structure and provide technical assurance for the work of less experienced practitioners, enabling them to maximise quality and velocity. Monitor the application of the methods and requirements, pro-actively managing technical risks and issues.
• Collaborating with practitioners from other disciplines (e.g. UCD, Engineering) to ensure the solution meets user and business needs.
• Take technical responsibility for the delivery of high-quality data science services on smaller engagements, across all stages (design, build, test, deploy, operate and continually improve), in line with best practice.
• Work with Delivery Managers to inform estimates for research and development activities, enabling them to plan technical activities, including how teams and work should be structured.
• Proactively identify and help mitigate technical risks, issues, assumptions and dependencies.
• Maintain relevant, up-to-date practitioner skills through training and accreditation, including a domain-relevant accreditation/certification at professional level.
• Being an active member of the Data Science discipline, identifying area for growth across the business, and providing coaching for less experienced practitioners

Senior Data Scientists enable the design, development, integration and testing of complex, high quality data science solutions and services to meet user needs, continually improving the application of best practice patterns, methods and tools. This includes:

• Build effective working relationships with client counterparts in your practitioner domain, and those of a partner / 3rd party organisation.
• Own the end-to-end implementation and design of data science models/components, seeking guidance and input from Lead and Principal Data Scientists where necessary.
• Help structure and provide technical assurance for the work of less experienced practitioners, enabling them to maximise quality and velocity. Monitor the application of the methods and requirements, pro-actively managing technical risks and issues.
• Collaborating with practitioners from other disciplines (e.g. UCD, Engineering) to ensure the solution meets user and business needs.
• Take technical responsibility for the delivery of high-quality data science services on smaller engagements, across all stages (design, build, test, deploy, operate and continually improve), in line with best practice.
• Work with Delivery Managers to inform estimates for research and development activities, enabling them to plan technical activities, including how teams and work should be structured.
• Proactively identify and help mitigate technical risks, issues, assumptions and dependencies.
• Maintain relevant, up-to-date practitioner skills through training and accreditation, including a domain-relevant accreditation/certification at professional level.
• Being an active member of the Data Science discipline, identifying area for growth across the business, and providing coaching for less experienced practitioners.