AI Data Scientist (KTP Associate)

KTP

Knowledge Transfer Partnerships (KTPs) are a unique UK-wide activity that help businesses to improve their competitiveness and productivity by making better use of the knowledge, technology and skills within universities, colleges and research organisations.

Further information is available at: https://iuk-ktp.org.uk/.

The Project

The University of Essex in partnership with RevWise Ltd offers an exciting opportunity to a graduate with the relevant skills and knowledge to design, trial and embed an agentic AI system for data management and communication optimisation.

Duties of the Post

The duties of the post fall under three key categories (Technical, People/change and Project Delivery) and will include:  

• Design, develop and deploy agentic AI systems to support data management, decision-making and communication optimisation within RevWise’s affiliate marketing operations.
• Stay up to date with emerging developments in agentic AI, large language models (LLMs), and autonomous systems, ensuring the project leverages state-of-the-art techniques.
• Work closely with RevWise stakeholders to ensure solutions are aligned with business needs and deliver measurable value.
• Support the implementation of a unified data strategy, ensuring consistent and high-quality data ingestion across the organisation.
• Take responsibility for the end-to-end delivery of the KTP project, ensuring milestones, timelines and objectives are achieved.
• Work collaboratively with the academic and company supervisors to monitor progress, manage risks and adapt plans where required. 

A full list of duties and responsibilities can be found within the job pack.

Key Requirements 

Qualifications 

• BSc in Computer Science, Mathematics, Data Science, or related fields. 

Experience/Knowledge 

• Experience of designing applied ML and agentic AI for prediction, automation and real-time decision support.
• Operational knowledge in distributed systems design, backend engineering and scalable event-driven architectures.
• Practical expertise with cloud platforms, containerisation, scalable DBs and modern languages (i.e. Python, JS, etc.).
• Experience handling large, complex datasets, including sales and customer data.
• Strong knowledge of machine learning.
• Experience designing, testing, and deploying AI and machine learning models in a controlled environment. 

Skills/Abilities

• Ability to quickly adapt to internal systems, data structures, and regulatory requirements.
• Strong commercial awareness, ensuring AI solutions align with commercial priorities.
• Excellent stakeholder engagement skills; able to explain technical concepts to non-technical audiences.
• Strong time management and organisational skills.
• Self-motivated, capable of working independently and in a team.

Benefits 

As a KTP Associate, the post will offer the following benefits: 

• A personal development budget of £5,667 (exclusive of salary).
• Management training and mentoring by an Innovate UK KTP Adviser.
• An interesting and challenging role, with exposure to a variety of stakeholders.
• Full access to university resources to complete the project.
• World-leading Academic and Company project supervision, with project support by a dedicated, sector leading KTP Office. 

Location 

RevWise Ltd, Innovation Centre, Knowledge Gateway, Boundary Road, Colchester, Essex, CO4 3ZQ

Please note that the role holder will be based at RevWise Ltd offices located in Colchester (hybrid working is offered) but may be expected to travel to the University of Essex Colchester Campus from time to time.

Please use the 'Apply' button to read further information about this role including the full job description and person specification which outlines the full duties, skills, qualifications and experience needed. You will also find details of how to make your application here. Our website http://www.essex.ac.uk contains more information about the University of Essex. If you have a disability and would like information in a different format, please email resourcing@essex.ac.uk 

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