Marketing Excellence Manager

Hyper Recruitment Solutions
Surrey
1 year ago
Applications closed

Related Jobs

View all jobs

Head of DevOps and DataOps

Head of Data Science

Senior Director, Data Science and Analytics

Senior Marketing Data Scientist

Lead Data Scientist - Pricing

Lead Data Scientist

Role Overview

We are currently looking for a Marketing Excellence Manager to join a leading Global Pharmaceutical company based in the Surrey area. As the Marketing Excellence Manager you will be responsible for optimising brand strategy and performance across the portfolio

Key Duties and Responsibilities

Your duties as the Marketing Excellence Manager will be varied however the key duties and responsibilities are as follows:

1. You will be working in partnership with the marketing team responsible for providing clear recommendations, data and insights to support priority brand customer journeys and strategy.

2. As the Marketing Excellence Manager you will be working in partnership with the brand teams to identify and quantify clear patient funnels and customer segments to maximise growth for the portfolio.

3. You will be working in partnership with the IS&E team to ensure the UK qualitative and quantitative primary market research needs for priority brands are developed to inform brand planning.

4. As the Marketing Excellence Manager you will be responsible for investigating and answering key business questions and working with IS&E to deliver the analytics and insights to support the adaptation of brand strategies and tactics.

Role Requirements

To be successful in your application to this exciting opportunity as the Marketing Excellence Manager we are looking to identify the following on your profile and past history:

1. Experience with data visualisation solutions (ex. Tableau) and other advanced analytic/data science solutions (ex. DSS) will be a plus.

2. Extensive experience in management of secondary data and familiarity with pharma applicable data is highly desired (ex. Midas)

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.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.