Pharmaceutical Machine Learning Specialist

Machine Learning specialist, strong stats background for global pharmaceutical company M4 Corridor. Python / R Your new company Is an innovative pharmaceutical company with a growing portfolio looking to add several skilled Machine Learning specialists at multiple levels to one of their groups. This group works with teams within the business focusing on model and method development and applying new approaches to draw insights out of clinical & research data to drive froward their drug development. Your new role The position is working within a team focused on statistical innovation and developing/applying machine & deep learning approaches to analyse data from drug discovery and development projects. This role can be partly home based. You will be an integral part of a wider project and R&D team, working with colleagues across a number of countries to ensure final delivery of multiple important projects. Main responsibilities will include a mix of: Acting as a technical lead on projects; Developing, validating and assessing ML methods, models, algorithms or approaches, with a particular focus on introducing/maintaining statistical rigour; Working with clinical and biological / pre-clinical researchers to analyse a variety of data sets, eg clinical trial, biomarker or genomic data; Investigating approaches / models used by external vendors to assess performance and look into issues such as overfitting, etc; Input into study design, research parameters and statistical analyses, including modelling approaches to find the optimal way of working; Hands-on programming in R, Python and/or SAS; Using data science, statistics or machine learning approaches to analyse and interpret clinical data sets; Data interpretation and visualisation; Working with colleagues and partners across multiple countries, sometimes as an 'ambassador' for the group. For those candidates interested in a contract position, there are similar contract roles available in the same team. What you'll need to succeed As well as strong communication skills for dealing with internal collaborators and stakeholders, you should have: An MSc (ideally PhD) in machine learning, statistics or computer science - or equivalent experience; Strong programming skills in R and/or SAS, Python or a similar language; A track record utilising a variety of statistical approaches to analyse data, eg Bayesian or multivariate approaches, with clinical trial exposure an advantage; Experience working with clinical trial or biological data sets is preferred but not essential; Strong hands-on experience utilising data science, machine learning approaches (random forest, neural nets, SVM, supervised / unsupervised learning, etc) or deep learning frameworks (Tensorflow, h2o); and Experience with data mining, statistics or data visualisation. Candidates who can demonstrate novel method, model or package development are encouraged to apply. What you'll get in return You'll get the chance to make a significant impact on the company's drug discovery and development projects, taking on project leadership for a number of different aspects. The company are relatively open on salary bands depending on the skills of the person coming in and the benefits package associated with the role is quite generous. The projects this group work on often involve exposure to very senior stakeholders (Global VP level) and so can offer excellent career advancement. What you need to do now If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call on . If this job isn't quite right for you but you are looking for a new position, please contact us for a confidential discussion on your career. Keywords: machine, learning, pharmaceutical, drug, discovery, development, clinical, trial, data, science, statistics, statistical, biomarker, discovery, genetics, Bayesian, machine, learning, programmer, programming, scientist, python, R, C, Bash, platform, project, manager, developer, tool, pipeline, computational, computer, oncology, neuroscience, immunology