Principal Statistician, Oncology Statistics

GSK
Stevenage
1 month ago
Applications closed

Related Jobs

View all jobs

Principal Quantitative Analyst - Sports Betting

Principal Quantitative Analyst - Sports Betting

Senior/Principal/Lead Data Scientist

Clinical Analytics Engineering, Senior Manager

Head, Medical Affairs Statistical Science

Machine Learning 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.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.