Principal Research Scientist

As a Principal Research Scientist, you will help us to achieve our goals and deliver success on behalf of our customers by researching and prototyping advanced statistical models, algorithms, and data workflows that improve Featurespace analytical products. You will help to build the external profile of Featurespace’s R&D and innovation programmes though academic and industry publications, events, and open-source contributions. Whilst also engaging stakeholders across the business to help identify analytical problems that Featurespace would benefit from solving.

This is a hybrid role based in our Cambridge office, so you will ideally be comfortable coming into the office once or twice a week. If you’re interested in the role but require more flexibility, please speak to us!

• Create fundamentally new analytical methodologies of relevance to the business
• Pioneer research into entirely new analytical tasks with little supervision, providing credible roadmaps to production
• Publish regular academic papers on relevant themes
• Lead working groups from across the business to identify and solve difficult technical challenges
• Impact and influence technical work across the company
• Interact closely with other teams to ensure releasable prototypes or publications
• Mentor more junior team members, share expertise and provide support when needed
• Contribute to the continuous improvement of team processes and shared workflows
• Break work into appropriately sized tickets with clear requirements and definitions of completion
• Build, maintain and adapt software used for research work across the Innovation Lab
• Scope and design prototypes to demonstrate analytical innovations
• Champion software engineering best practices and processes across the Innovation Lab
• Identify and manage technical debt to improve pipeline quality
• Review code to impart knowledge and good practice to others

Must haves:

• Academic background at PhD or higher in a relevant discipline, e.g. Computer Science, Mathematics, Statistics, Physics, or Engineering
• Research experience with publications advancing theoretical knowledge in Machine Learning
• Be a natural teacher, who effectively engages people at all levels
• Experience in using Python, Java, C++ or another major programming language for algorithm development
• Ability to manage and prioritise personal workload
• Ability to cast diverse business context as a mathematical problem

Great to haves:

• An established academic profile in a relevant field of machine learning
• Experience with deep learning frameworks such as TensorFlow, PyTorch
• Knowledge of statistical privacy-enhancing technologies, such as federated learning or differential privacy
• Experience with modern IDEs, version control system (git)
• Experience in working with large data sets
• Experience with Bayesian inference and other statistical methods

Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.