Strategic AI Data & Insights Partner

M&I

Greater London

On-site

GBP 65,000 - 90,000

Full time

7 days ago

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Benefits offered by this job

Competitive Salary

London office near Borough Market

28 days holiday plus bank holidays

Regular employee social events

Bupa private health insurance (company

Employee Assistance Program

Enhanced maternity and paternity leave

4 pm Friday finish

Job summary

AI Data & Insights Officer (FTC) at Worldwide Events Group is a hands-on, business‑facing role at the intersection of data analysis, BI, AI enablement and commercial decision‑making, based in the Borough of South London. You will access Salesforce, event platforms, marketing systems and operational tools to improve data quality, support RAG and identify commercial opportunities.

This six‑month fixed‑term contract reports to the Head of AI Implementation and offers potential extension, with a

Qualifications

Professional experience in data analysis, business intelligence, analytics engineering or a closely related role.
Strong experience of data preparation, cleansing, modelling and quality assurance.
Experience using SQL and visualisation tools such as Power BI, Microsoft Fabric or equivalent platforms.
Experience working with CRM, customer, commercial or operational data; Salesforce experience is particularly relevant.
Ability to combine information from multiple systems and work effectively with APIs or structured data integrations.
Strong understanding of KPI design, dashboarding and the communication of actionable insight.
Ability to translate complex evidence into clear business recommendations.
Excellent problem-solving, critical-thinking and attention-to-detail skills.
Strong communication and stakeholder-management skills.
Sound understanding of data privacy, access control and responsible use of business information.
Curiosity about AI, automation and the practical application of emerging technology.

Responsibilities

Develop and maintain datasets, models and insights that support AI agents and business decision‑making.
Consolidate, cleanse and structure information from Salesforce, event platforms, marketing systems and operational tools.
Define practical data‑quality, metadata and governance standards for information used by Agent Factory.
Identify trends, risks and commercial or operational opportunities within WWE datasets.
Support secure, reliable data flows between approved systems and agent solutions.
Create and maintain knowledge bases and retrieval structures that improve agent accuracy and usefulness.
Support the design, testing and optimisation of RAG capabilities across the Agent Factory ecosystem.
Prepare evaluation datasets and test cases for assessing agent outputs.
Work with Agent Engineers and Agentic Capability Engineers to translate business data into reusable agent skills, tools and intelligence services.
Monitor data‑related failure patterns and recommend improvements to source content, retrieval and agent behaviour.
Design dashboards, scorecards and reporting that provide meaningful visibility of business performance.
Define and track measures for agent adoption, accuracy, time saved, operational impact and commercial value.
Evaluate the effectiveness and return on investment of AI agents and automations.
Develop actionable insight for leadership and business teams rather than producing reporting for its own sake.
Establish repeatable methods for monitoring and communicating the value created by Agent Factory.
Develop insight that supports customer retention, buyer and supplier engagement, sales effectiveness, event performance and workflow improvement.
Explore predictive and segmentation approaches where they can support better business decisions.
Turn analytical findings into clear recommendations, prioritised opportunities and defined next actions.
Help teams move from descriptive reporting towards decision intelligence and next‑best‑action capabilities.
Work with departments across WWE to understand their data, reporting and insight requirements.
Translate business questions into clear analytical work and practical data products.
Present complex findings in a concise, accessible way to technical and non‑technical audiences.
Promote responsible, evidence‑led use of data and AI across the organisation.
Document analytical methods, data definitions and reusable assets so capabilities can scale.