Our client is growing at pace due to the success of their Industry leading products for clinical trials. We are looking for a statistician.

The statistician will be involved in working with the Product Development team in the design and development of new releases of my clients market leading risk based monitoring product. We are currently re-building the platform with a view to making the application more comprehensive and build in more statistical monitoring methods. The main role of the Statistician will be to develop statistical models and visualizations that can be used to identify potential data quality issues with subjects, sites and studies. Areas that we are currently evaluating are:

• Statistical approaches to working with small data sets (that would be applicable to Phase ½ trials)
• Quality Tolerance Limits using process control methodology
• Bayesian models using historical data sets to inform tolerance limits for new studies
• Trend Analysis
• Site comparison models
• Cross study comparison models

This role will also be involved in advising on test strategies for the models.

As we progress with the new build it is our intention to move into more automated modelling using machine learning, so this will provide a great opportunity for anyone interested in developing skills in this area.

Study Implementation

• The role will in part be a client facing role, the statistician will be involved in the initial protocol risk assessment, evaluating the study design and statistical analysis approach for risk and bias. Following on from this the statistician will also work with the QRBM Implementation Consultants to define Key Risk Indicators for the Centralized Monitoring strategy, and once set up, to determine control thresholds/tolerance limits. Once the study is underway, the statistician will also be involved in the ongoing review, providing support and guidance to client and RBM Implementation Consultants on data interpretation and adjustments to study tolerance limits/thresholds. My client are passionate about learning from experience and listening to our customers, and it is important that the statistician is involved in the implementation process to bring the lessons learned from our study projects into the product development.

This is a great opportunity for someone who is interested in how we can make better use of data in clinical trials to determine which sites, patients and data are most at risk with a view to being able to identify the leading indicators that are predictive of study and site quality.

My client are passionate about our culture and values and we are looking for someone who will thrive in a hardworking, energetic, creative and team-oriented environment. Ideally you will be excited by the opportunity to have a leading role in the implementation and development of statistical approaches in centralized monitoring, direct access to the senior leadership team, and the opportunity to be involved in the implementation and continuous development of an application that will truly make a difference to advancements in getting medical treatments to patients.

The Candidate

Experience in data modelling, using statistical methods to identify behavioral and data patterns. Industry experience would be advantageous, but this is no clinical endpoint analysis so a different way of thinking about data and stats modelling is required.

An interest and/or experience in machine learning models would also be an advantage but not essential.

Interpersonal Skills

• Self-motivated
• Creative and visionary
• Strong communication, ability to make a positive impact with internal and external stakeholders
• Enjoy working in a small, but growing, results-oriented team
• Ability to take responsibility for the consistency and quality of deliverables

Technical Skills (not exclusive)

• PhD or MSc in Medical Statistics, Statistics or Data Science
• Desirable to have an understanding of Agile software development
• Experience in modeling and regression analysis
• Programming skills ideally in R, Python and SAS
• Experience/interest in application of Machine Learning
• Ability to review clinical protocols and understand the study design and subject visits schedules
• Ability to demonstrate and apply critical thinking to KRI and data visualization design and centralized monitoring implementation
• Understanding of clinical trial data and data structure, particularly from EDC, including CDISC/CDASH and SDTM standards
• Ideally an understanding of other standards in Healthcare such as Snowmed, Bridg, HL7

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