Commercialisation and Omnichannel Excellence Lead

Sobi

Cambridge

10 months ago

Applications closed

Job Description

We are seeking a visionary and experienced Commercialisation and Omnichannel Excellence Lead to join the regional team. This new role will bring together a broad set of capabilities that will innovate and improve our customer journey model. It will be pivotal in driving implementation of the product global strategies and the excellence in execution processes for new product launches and on-going activities with global teams. Supporting the region(s) in their journey of channel maturity and integration across the customer journey, ultimately enhancing omnichannel engagement via the seamless integration of digital and traditional channels.

Key Responsibilities:

Develop and implement commercial strategies to maximize market reach and improve patient outcomes.
Serve as the Commercialization & Omnichannel Excellence Representative in the European Leadership Team providing guidance and leadership in all commercial excellence processes to the Genera/Country Managers, BUDs and Brand Managers.
Enhance omnichannel engagement by integrating digital and traditional marketing channels. Stay up to date with the latest technology and best practices. Anticipating and piloting future capabilities e.g. GenAI & pattern recognition via Machine learning
Deploy and manage digital channel maturity, capable of measuring ROI (both top line and bottom-line impact) and setting appropriate KPIs.
Foster a culture of excellence and continuous improvement within the organization. Collaborate with internal and external stakeholders to drive strategic initiatives.
Shape training programs and Key Account approach to deliver excellence in customer journeys. Operational leadership of Account management, Business acumen and culture of performance.
In collaboration with the affiliate business units, Training and Business operations, develop and implement clear excellence in operational processes and tools to enable the effective and efficient delivery of key activities for all customer facing colleagues.
Leading and developing a team of above country digital leads to deliver on channel deployment and utilisation. Sharing best practices across Global Brand team and affiliates
Build strong network with teams in Training and learning development, IT/ CRM Veeva, Medical Affairs, Marketing and other relevant departments to anticipate and support product commercialization activities

Qualifications

Experiences:

Over 10 years of proven experience in commercial strategy and implementation of omnichannel marketing within the pharmaceutical industry
Experience in successfully launching new products in a regional capacity
Consultancy background and experience of change management projects across pharmaceutical companies
Multiple examples of moving from vision to implementation
Engineering, financial or statistical educational background

Competencies:

Ability to work effectively across diverse markets and cultures.
Excellent communication and interpersonal skills
Strong leadership and team collaboration skills
Passion for advancing healthcare and improving patient outcomes

Join us in our mission to transform healthcare and make a meaningful impact on patients' lives globally.

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

Industry Insights

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

Jan 18, 2026

Careers Jobs

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.

Jan 13, 2026

Jobs

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.

Jan 6, 2026

Education Jobs

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.