Principal Statistician (417810 Upper Providence)

慨正橡扯; Philadelphia (Philadelphia County); On-site; USD 80,000 - 120,000; Full time

Job summary

An innovative biopharma company seeks a skilled statistician to join their dynamic team. In this exciting role, you will collaborate with scientists to design experiments, analyze complex data, and apply advanced statistical techniques to drive drug discovery. You will be part of a dedicated group focused on improving human health through rigorous statistical analysis and creative problem-solving. If you have a passion for statistics and a desire to make a meaningful impact on the health of millions, this opportunity is perfect for you. Join us in our mission to advance science and improve lives through innovative research.

Qualifications

• PhD in statistics or biostatistics with formal training required.
• 1 year experience in advanced statistical modeling and machine learning.

Responsibilities

• Work with scientists to define objectives and propose statistical strategies.
• Analyze data using statistical methods and develop novel techniques.

Skills

Advanced statistical modeling

Machine learning techniques

R programming

SAS programming

Communication skills

Problem-solving

Education

PhD in statistics or biostatistics

Tools

R

SAS

Job description

We are a biopharma company focused on uniting science, technology, and talent to get ahead of disease together. By the end of the decade, we aim to positively impact the health of 2.5 billion people as a successful, growing company where people thrive.

Why Research Statistics?

We play a key role in GSK’s discovery of new medicines, collaborating with outstanding scientists to advance innovative ideas in drug discovery. We design experiments, analyze data, and visualize results for projects that range from small studies with single endpoints to high-dimensional genomic data. We use classical statistical methods, Bayesian techniques and modern machine learning algorithms. Our work is varied and challenging with the common goal of advancing the science of human health.

Our team is part of GSK’s Biostatistics function – a large group of statisticians, programmers, and data scientists with the mission to put statistical thinking at the heart of R&D decision-making. Our colleagues design and analyze clinical trials, but we focus on laboratory experiments and the re-analysis of randomized and observational data to identify targets, biomarkers, and patient sub-populations. To succeed, our team members need good technical and communication skills and the ability to learn rapidly, to develop practical solutions, and to apply statistical techniques in creative ways. Our staff enjoy solving challenging problems and developing the skills and knowledge together to improve the health of millions of people.

Key Responsibilities

1. Work with scientists and leaders to identify and define scientific objectives that benefit from statistical approaches and propose implementation strategies.
2. Examine relevant literature and perform simulations to assess the applicability of statistical methods to challenges in drug discovery.
3. Craft experiments with clear objectives that address important scientific queries.
4. Analyze data using established statistical methods and develop novel methods to address important scientific questions.
5. Clearly communicate results to fellow researchers and managers at all levels.

Why You?

Basic Qualifications & Skills:

We are looking for professionals with these required skills to achieve our goals:

1. PhD in statistics, biostatistics, or a closely related field with formal statistical training.
2. 1 year experience of proven innovation and technical strength in advanced statistical modelling and/or modern machine learning techniques.
3. At least 3 years of experience writing code in R or SAS.

Preferred Qualifications:

The following skills are not required, just preferred:

1. Ability to clearly communicate both new and established statistical methods to scientific colleagues in spoken and written English.
2. Successful statistical consulting experience, working alongside researchers from other fields to devise practical solutions for scientific inquiries.
3. Skilled in selecting, using, modifying, and developing statistical methods to address complex scientific questions effectively.
4. Continuous learner, regularly expanding statistical and scientific knowledge.
5. Experience using at least some of these statistical methods: experimental design, mixed models, Bayesian statistics, linear and nonlinear regression, repeated measures, machine learning algorithms, and high-dimensional data analyses.
6. Knowledge of or interest in genetics, molecular biology, pathobiology, the process of drug discovery, as well as cellular and tissue-based model systems.