Audience Intelligence Lead London, England United Kingdom

Tbwa Chiat/Day Inc
London
11 months ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer

AI & Data Science Manager / Senior Manager

Data Analyst - Government Digital Service - SEO

Data Analyst - Government Digital Service - SEO

Senior Data Scientist - AI Practice Team

Data Scientist

Established in 2004,OLIVERis the world’s first and only specialist in designing, building, and running bespoke in-house agencies and marketing ecosystems for brands. We partner with over 300 clients in 40+ countries and counting. Our unique model drives creativity and efficiency, allowing us to deliver tailored solutions that resonate deeply with audiences.

As a part ofThe Brandtech Group, were at the forefront of leveraging cutting-edge AI technology to revolutionise how we create and deliver work. OurAI solutionsenhance efficiency, spark creativity, and drive insightful decision-making, empowering our teams to produce innovative and impactful results.

Location:London, England, United Kingdom (2 days a week from our London offices)

About the role:

The Audience Intelligence Lead joins at an exciting time as we evolve our approach to understanding audiences and designing experiences for them. This role will drive forward the use of data across social, search, and advanced analytics to enhance our overall capabilities and the services we offer. Are you ready to lead innovation in audience engagement with us?

What you will be doing:

  • Lead Audience Intelligence Solutions:Act as the principal expert in all Audience Intelligence solutions, providing oversight on projects and serving as the key liaison for clients and internal stakeholders. Champion insight practices and build innovative solutions to enhance client offerings.
  • Data Management and Analysis:Utilise premier tools like Brandwatch and GWI to construct advanced Boolean queries, manage extensive dashboards, and develop custom audiences for targeted analysis. Interrogate data and cross-reference with other sources to extract meaningful audience insights.
  • Social Media Management Expertise:Command expertise in platforms such as Quintly, Sprinklr, and others to manage social analytics for paid and organic frameworks and influencer marketing. Drive execution of comprehensive reporting, dashboarding solutions, and audits.
  • Data Storytelling and Reporting:Organise and interpret data for effective reporting, develop strategic data narratives, and present insights aligned with business strategies. Apply techniques like semiotics and psychographics to enrich audience understanding.
  • AI and Business Expertise:Act as a champion for AI by staying informed on AI solutions and industry advancements, applying new tools and practices to continually enhance project and process outcomes. Lead thought leadership initiatives to drive team and business knowledge forward.
  • Project Leadership and Vendor Management:Oversee project scoping, costing, and retrospection in collaboration with the Insight & Effectiveness Director. Maintain vendor relations, onboard new technologies, and champion the integration of Audience Intelligence into the broader business landscape.
  • Team Development and Process Improvement:Offer support, training, and enhancement of internal processes to improve project execution. Lead internal and client meetings, developing solutions for growth and operational efficiency.

What you need to be great in this role:

  • Technical Proficiency: Mastery of tools like Brandwatch, GWI, and social media management suites. Strong skills in Excel, Google Sheets, search data analytics, and dashboarding solutions.
  • Leadership and Communication: Ability to lead teams with positivity and professionalism. Excellent capability in holding meetings, leading client calls, and conducting training sessions. Confident when managing client expectations and delivering comprehensive insights.
  • Analytical and Strategic Thinking: Demonstrated strength in data analysis, interpretation, and building insightful narratives. Competency in developing strategic frameworks for social insights and business intelligence.
  • Project and Time Management: Exceptional organizational skills with the ability to deliver projects independently and manage resources efficiently. Expertise in conducting project reviews, setting objectives, and maintaining alignment with broader business goals.
  • Proficient in Large Language Models (LLMs) and AI insight tools: Solid hands-on experience with LLMs and AI technologies, paired with a comprehensive understanding of their applications. Competent in critiquing and providing best practices to optimize the use of AI tools for maximum effectiveness.
  • Continuous Learning and Adaptability: A proactive mindset geared towards learning and adopting new market tools and practices. Display creativity and foresight in implementing innovative solutions that keep the team and business at the cutting edge.
  • Collaboration and Team-Oriented Attitude: Strong collaborator who engages on both professional and social levels with team members. A team player who values feedback and fosters an environment of mutual respect and learning.
  • Commercial Insight: Sharp commercial acumen with an ability to offer solution-driven insights that balance business objectives with client needs.

Our values shape everything we do:

BeImaginativeto push the boundaries of what’s possible.

Bealways learning and listeningto understand.

Beactively pro-inclusive and anti-racistacross our community, clients, and creations.

OLIVER, a part of the Brandtech Group, is an equal opportunity employer committed to creating an inclusive working environment where all employees are encouraged to reach their full potential, and individual differences are valued and respected.

OLIVER has set ambitious environmental goals around sustainability, with science-based emissions reduction targets. Collectively, we work towards our mission, embedding sustainability into every department and through every stage of the project lifecycle.

Apply for this job

* indicates a required field

J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.