Principal Statistician, Oncology Statistics

GSK
London
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Data Engineer (GCP)

Principal Data Analyst

Principal Data Engineer

Principal Data Engineer (MS Azure)

Principal Data Architect DV Cleared

Principal Data Engineer

Job description
Site Name:USA - Pennsylvania - Upper Providence, GSK HQ, Stevenage, Waltham
Posted Date:Jan 24 2025

Clinical Statisticians are highly prized and urgently needed at GSK to grow an industry-leading team to ensure high quality quantitative reasoning is at the heart of every project in the portfolio. Our role is essential to ensure we maximize the use of every single data point available to efficiently determine translational strategies that are the foundation of our end-to-end clinical development plans. We need exceptionally talented and committed Statisticians like you to apply your statistical skills and innovative statistical methodology to drive key contributions to the development of new medicines.

The OncologyClinical Development Statisticsgroup have a Principal Statistician opportunity available to support assets within the Oncology disease area, providing statistical and strategic insight into the clinical development plan and design of end-to-end development strategies. This begins with early first in human trials, all the way through to late phase drug development. The team strive to use novel clinical trial designs and innovative statistical methodologies, including Bayesian techniques, to quantify risk across an entire program and enable smart decision making on where to invest to improve the probability of study and program success.

Key Responsibilities:

  • Provide required statistical support to Project and Study Statisticians across the oncology team.

  • Provide statistical input to the design, analysis, reporting and interpretation of clinical studies using a wide range of statistical approaches and/or applicable software (e.g. simulation, Bayesian methods, interim analysis strategies).

  • Author statistical analysis plans and prepare statistical input to key documents and presentation material.

  • Apply standard processes to tasks to ensure that deliverables are accurate, high quality and meet agreed timelines.

  • Build and maintain effective strategic working relationships with internal and external partners to meet business needs.

  • Identify, develop, and implement novel statistical methodologies in support of medicines development.

Basic Qualifications:

  • PhD in Statistics or related discipline, or MS in Statistics or related discipline with 3+ years of experience working as a Statistician within a CRO, Clinical Trial, or Academic setting in the Pharmaceutical Industry

  • Experience implementing innovative methods, such as Adaptive Design, Machine Learning, and Trial Simulation using SAS, R or other professional software

Preferred Qualifications:

  • Practical understanding of Statistical Modelling and its application to Real World clinical problems

  • Experience with Bayesian methods

  • Expertise and practical application in multiple statistical methodologies

  • Self-motivated and independent worker

  • Strong time management skills; able to effectively organize and manage a variety of tasks across different projects

  • Capable of applying innovative statistical thinking

  • Track record of strong performance in an academic or industry setting

  • Excellent interpersonal and communication skills

  • Capability in building and maintaining strong working relationships in a team setting

  • Demonstrated ability to explain novel and standard methods to scientific and clinical colleagues.

  • Strong influencing skills applied effectively across functions and levels of an organization

  • Time management and prioritization skills

#LI-GSK

Please visit GSK US Benefits Summaryto learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

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 organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

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 place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).

GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, 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.

Important notice to Employment businesses/ Agencies

GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.

Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit GSK’s Transparency ReportingFor the Recordsite.

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.