AI Data Scientist (KTP Associate), Essex Business School

University of Essex; United Kingdom; On-site; GBP 30,000 - 40,000; Full time

Job summary

A leading UK university is seeking a KTP Associate to use AI and data insights to transform business operations. This role involves analyzing data flows, developing machine learning models, and enhancing decision-making processes. Ideal candidates will have a postgraduate degree in Data Science and experience with applied machine learning. Competitive benefits include a personal development budget and access to university resources.

Benefits

Personal development budget of £5,340

Travel & Subsistence budget of over £4,000

Management training and mentoring

Access to university resources

Qualifications

• Proven experience in applied machine learning, including supervised and unsupervised learning techniques.
• Solid understanding of data governance and quality.

Responsibilities

• Analyse and map data flows to identify inefficiencies.
• Develop and deploy machine learning models for various applications.
• Clean and integrate datasets for analytics.

Skills

Applied machine learning

Data manipulation skills

Strong analytical skills

Excellent communication skills

Enthusiasm for innovation

Education

Postgraduate degree in Data Science or related field

Tools

Python

AI/ML libraries (Numpy, Pandas)

Cloud platforms (Microsoft Azure)

Git

Job description

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 Storm Technologies offers an exciting opportunity to a graduate with the relevant skills and knowledge to transform business operations and processes by leveraging AI and data insights, identifying inefficiencies, and implementing systems that drive data-driven decision-making, while fostering a culture of continuous improvement within the organisation.

DUTIES OF THE POST

The duties of the post will include:

• Analyse and map data flows across supply chain, sales, and customer processes to identify inefficiencies and optimisation opportunities.
• Develop, test, and deploy machine learning models for product recommendation and cross-selling, customer segmentation and churn prediction, and inventory forecasting and supplier risk scoring.
• Clean, transform, and integrate diverse datasets from ERP, CRM, and other systems to create actionable analytics pipelines.
• Work closely with internal stakeholders (e.g., sales, procurement, operations) to understand business needs and align data science solutions with strategic goals.
• Create interactive dashboards and decision support tools (e.g., in Power BI or Tableau) to visualise insights and improve decision-making.
• Build internal capability by documenting workflows, delivering training, and supporting the adoption of new tools by non-technical users.
• Collaborate with academic supervisors to ensure technical rigour and contribute to research outputs (e.g., journal articles or case studies). Acting as project lead, to progress the project(s) and ensure milestones are met to a timely manner.
• Embedding technology, training and upskilling company staff.
• Participating in academic and/or industrial conferences and other events, to disseminate and present research outcomes to the wider community.

These duties are a guide to the work that the post holder will initially be required to undertake. They may be changed from time to time to meet changing circumstances.

KEY REQUIREMENTS

Qualifications / Training:

• A postgraduate degree in one of these areas: Data Science; Artificial Intelligence / Machine Learning; Business Analytics; Computer Science; Information Systems.

Experience / Knowledge:

• Proven experience in applied machine learning, including supervised and unsupervised learning techniques.
• Strong data manipulation and analytical skills using Python and basic ML libraries such as Numpy, Pandas, Matplotlib, SciPy, and Scikit-Learn.
• Solid understanding of data governance, data quality, and integration principles.
• Skills in risk assessment, stakeholder management, and quality assurance.
• Experience in deploying AI/ML models in real-world commercial settings
• Familiarity using cloud platforms such as Microsoft Azure.
• Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search and similarity-based retrieval.
• Practical understanding of Retrieval-Augmented Generation (RAG) workflows, including integration of external knowledge sources into LLM pipelines.
• Experience in working with LLMs and developing Agentic AI models.
• Experience in version controlling such as Git.

Skills / Abilities:

• Excellent communication skills, with the ability to translate complex technical ideas into actionable business insights.
• Ability to work independently while integrating into a wider team.
• Enthusiasm for innovation and continuous improvement.

A full list of applicant requirements (including any additional desirable criteria) can be found in the job pack.

BENEFITS

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

• A personal development budget of £5,340 (exclusive of salary).
• A combined Travel & Subsistence and Consumables budgets of over £4,000.
• 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

Storm Technologies
The Boulevard
2 Blackmoor Lane
Croxley Business Park
Watford
Hertfordshire
WD18 8YW

Please see the attached job pack, which contains a full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role plus more information relating to the post. We recommend you read this information carefully before making an application. Applications should be made on-line, but if you would like advice or help in making an application, or need information in a different format, please contact [e-mail]

*More information: Working at the University