Head of Data Science Innovation for R&D Operations in London

Head of Data Science Innovation for R&D Operations in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
GlaxoSmithKline

At a Glance

  • Tasks: Lead innovative data science projects to transform R&D decision-making and enhance medicine development.
  • Company: GSK, a global healthcare leader dedicated to improving lives through science and technology.
  • Benefits: Flexible working culture, competitive salary, and opportunities for personal and professional growth.
  • Other info: Be part of a diverse team committed to innovation and making a real difference.
  • Why this job: Join a dynamic team driving cutting-edge data solutions that impact global health.
  • Qualifications: Masters or PhD in a quantitative field with experience in drug development and data science.

The predicted salary is between 80000 - 100000 £ per year.

GSK is a place where outstanding people do amazing things. As a science-led global healthcare company, we exist to help people do more, feel better, live longer. Our goal is to be one of the most innovative, best performing, and trusted healthcare companies.

This is an exciting opportunity to channel your passion for Innovation in the field of Statistics and Data Science to help shape the future of the Biostatistics function and transform the way in which GSK uses data and quantitative thinking to drive decision-making in R&D.

Biostatistics is the single-largest functional group of Statisticians, Programmers and Data Scientists within GSK R&D, numbering approx. 900 permanent people in the US, UK, Europe and India. Our mission is to put statistical thinking at the heart of R&D decision-making; to ensure that predictive models and well-designed experiments and trials deliver robust evidence as the input to those decisions – ultimately making the R&D process more efficient and increasing the probability of success.

We are investing in our cutting-edge innovation capabilities by expanding the Statistics & Data Science Innovation Hub (SDS-IH) led by Prof Nicky Best. The vision of SDS-IH is to be the catalyst for innovation and advanced data-driven decision making. To achieve this, we are forming agile teams dedicated to untangling and resolving complex data challenges across R&D, constructing robust data pipelines, comprehensive analytics, and dynamic dashboards to enable stakeholders to take data-informed decisions in real-time.

At the heart of SDS-IH lies a diverse coalition of Statisticians and Data Scientists - a synthesis of unique skills and experiences. Together, we are the architects of novel quantitative methodologies, systems, and tools – a living embodiment of our vision.

Why join The Statistics & Data Science Innovation Hub?

SDS-IH is now poised to take a leap forward and we are looking for an entrepreneurial statistician/data scientist to join us as Head of Data Science Innovation for R&D Operations to help us supercharge quantitative decision-making across R&D. Our goal is to interconnect and amplify current data and modelling initiatives, fundamentally transforming and accelerating the landscape of medicine development by creating a framework to enable the consistent and scalable use of data across R&D. We envision a future where an advanced, partially automated system seamlessly orchestrates end-to-end clinical development plans. This system will not just streamline processes; it will set new benchmarks in efficiency, accuracy, and innovation in the journey of medicine and vaccine development from laboratory to patient.

Responsibilities

  • Support the design and implementation of a framework to enable the consistent and scalable use of data across R&D and develop an advanced, partially automated system for orchestrating end-to-end clinical development plans, in collaboration with other pillars within SDS-IH and relevant R&D line functions.
  • Build strategic relationships with business and operations partners across R&D (e.g. Clinical Operations, Clinical Supply Chain, Portfolio Analytics, Finance, HR, Regulatory, Resource Management) to identify and implement opportunities to apply predictive models to make data-informed decisions in pursuit of business goals.
  • Proactively seek opportunities across R&D to leverage innovative statistical and data science methods (including gen AI) to drive business improvements and run prioritized experiments to identify ideas with high-level business impact.
  • Lead and inspire teams of Statisticians and Data Scientists to deliver functional products, using agile and other principles as appropriate.
  • Ensure the team delivers real business value through the deployment and maintenance of statistical/ML models into GSK’s production ecosystem (aka MLOps).
  • Member of the SDS-IH Leadership Team with accountability for developing and driving the SDS-IH strategy to connect and scale predictive modelling capabilities for enhanced efficiency, with a focus on the interplay between various business and clinical operations and ensuring alignment of priorities with the overall SDS-IH group and wider Biostatistics’ and company’s strategic goals.

Basic Qualifications

  • Masters in data science, statistics, computer science, mathematics, engineering or related quantitative discipline.
  • Extensive experience in drug development, clinical trials, clinical operations and regulatory compliance.
  • Demonstrable evidence of entrepreneurship with proven record of achieving business impact through data-informed insights and delivery of innovative data science products.
  • Considerable leadership experience in planning and directing projects and effectively prioritising goals.
  • Demonstrable evidence of learning agility and unbiased approach to solving modelling and prediction problems using appropriate tools and methods.
  • Experience writing and delivering R and/or Python packages into production: version control; testing; CI/CD; environment management through containers and/or virtual environments.
  • Effective verbal and written communication and stakeholder engagement conveying complex concepts to diverse audiences and managing cross-departmental relationships.

Preferred Qualifications

  • PhD (preferred) in data science, statistics, computer science, mathematics, engineering or related quantitative discipline.
  • Demonstrated understanding of organizational dynamics in a matrix environment preferred.

Why Us?

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We’re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.

As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to neurodiversity, race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

Head of Data Science Innovation for R&D Operations in London employer: GlaxoSmithKline

GSK is an exceptional employer that fosters a culture of innovation and collaboration, particularly within the Statistics & Data Science Innovation Hub. Employees benefit from a dynamic work environment that encourages professional growth through cutting-edge projects in R&D, while also enjoying flexible working arrangements and a commitment to diversity and inclusion. Joining GSK means being part of a mission-driven team dedicated to transforming healthcare and making a meaningful impact on global health.

GlaxoSmithKline

Contact Details:

GlaxoSmithKline Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Head of Data Science Innovation for R&D Operations in London

Tip Number 1

Network like a pro! Reach out to people in your field, especially those at GSK or similar companies. A friendly chat can open doors and give you insights that a job description just can't.

Tip Number 2

Prepare for interviews by diving deep into GSK's mission and values. Show us how your passion for data science aligns with our goal of transforming healthcare. Tailor your examples to highlight your innovative spirit!

Tip Number 3

Don’t just wait for job openings; create your own opportunities! Share your ideas on social media or professional platforms about how data science can revolutionise R&D. This could catch the eye of someone at GSK.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining our team and contributing to our mission of making a real impact in healthcare.

We think you need these skills to ace Head of Data Science Innovation for R&D Operations in London

Data Science
Statistics
Predictive Modelling
Clinical Trials
Drug Development
Leadership
Agile Methodologies

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data science and innovation. We want to see how your skills align with the role of Head of Data Science Innovation for R&D Operations, so don’t hold back on showcasing your relevant achievements!

Showcase Your Passion:Let your enthusiasm for data science and its impact on healthcare shine through. We’re looking for someone who’s not just qualified but also genuinely excited about transforming R&D processes. Share any personal projects or initiatives that demonstrate your passion!

Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to convey your ideas and experiences. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role.

Apply Through Our Website:Don’t forget to submit your application through our official website! This ensures that your application is processed correctly and gives you the best chance to stand out. Plus, it’s super easy to do – just follow the prompts!

How to prepare for a job interview at GlaxoSmithKline

Know Your Data Science Stuff

Make sure you brush up on your data science and statistical knowledge. Be ready to discuss specific methodologies you've used in past projects, especially those that relate to drug development and clinical trials. GSK is looking for someone who can demonstrate a deep understanding of how data science can drive decision-making in R&D.

Show Your Leadership Skills

As the Head of Data Science Innovation, you'll need to inspire and lead teams. Prepare examples of how you've successfully led projects or teams in the past. Highlight your experience in agile methodologies and how you've fostered collaboration across departments to achieve business goals.

Connect with Their Vision

GSK has a clear vision for innovation in R&D. Familiarise yourself with their mission and values, and think about how your personal goals align with theirs. During the interview, express your enthusiasm for their vision and how you can contribute to transforming the landscape of medicine development.

Prepare for Technical Questions

Expect technical questions related to predictive modelling, MLOps, and the tools you’ve used (like R or Python). Be ready to discuss your experience with deploying models into production and any challenges you've faced. This will show that you not only understand the theory but also have practical experience in applying it.