Statistician

Reading, Berkshire
AWE
AWE is currently recruiting for a Statistician for the Energetic Materials Group within the Explosive Materials and Initiation Science Group within MAS. This role offers an excellent opportunity for anyone looking to develop their skills and gain an insight into regulatory sciences. Statistician Location: Reading Salary: £42,520 – £67,200 (dependant on suitability and level of experience) Closing Date: 21st June 2023 As part of our People Promise, AWE (one of the best 25 big companies to work for in the UK) has a range of benefits to suit you. These include: Time to recharge your batteries with 270 hours of annual leave (plus every other Friday off work) Consideration for flexible working arrangements so that your work may fit in with your lifestyle. Just let us know on your application if you wish to work part time Opportunities for Professional Career Development that include funding for the annual membership of a relevant professional body, access to mentors and training Employee Assistance Programme and Occupational Health Services A generous defined contribution Group Personal Pension (we will pay between 9% and 13% of your pensionable pay depending on your own contribution) Life Assurance Discounts – access to savings on a wide range of everyday spending Special Leave Policy including paid time off for volunteering, public service (including reserve forces) and caring for your family A host of voluntary & core benefits to suit your health and wellbeing – more information available on our careers site There are three main components to this unique and important role: To define the statistical strategy for the group, driving improvements in data analysis, uncertainty quantification, and test validation To add rigour and quantification to assessments undertaken by the group on explosives safety, performance, and reliability To develop statistical tools and models to enhance materials understanding and enhance the leverage of extant and new data sources. We would be interested in hearing from candidates who can demonstrate knowledge or experience in some of the following: Degree in a STEM discipline, equivalent NQF level 6 qualification or equivalent experience Substantial experience working with scientific/engineering/academic teams focusing on applied statistics Ability to develop code in languages like R, Python, MATLAB, C++, FORTRAN Ability to integrate and work well in a team and support or take the technical lead in projects Ability to convey complex and highly technical issues to diverse audiences Candidates would also benefit from having any of the following: Structured approach to problem solving Understanding of applied statistics best practice Familiarity with common libraries for statistical analysis, data assessment and machine learning Ability to develop code (such as statistical analysis in R) in appropriate software Ability to capture technical requirements and produce appropriate implementations Familiarity with software development lifecycle Candidates must be willing and able to obtain and maintain the necessary security clearance for the role