Machine Learning & Data Analytics Specialist
- Role Type
Any Ricardo office globally
- Closing Date
This position supports Ricardo’s strategic shift towards Digital Engineering – the successful candidate(s) will be embedded with existing Ricardo teams to identify new data analytics opportunities, explore analysis options, build case studies, support business development activities and execute/lead associated project work for customers.
You will be expected to work autonomously with guidance from both engineering specialists and other Ricardo colleagues in order to:
rapidly test concepts, followed by iteration and refinement through to “ready for pilot”,
understand how to interface learning based analysis methods to add capability and new services to support/expand our consulting business
support evaluation of best-case applications for learning based analysis in core business areas for Ricardo such as product research/development/validation and maintenance /large database information associated with our mobility, energy and resources business.
This is a role for someone who is looking to develop themselves and become recognised as a leader within the Digital Engineering community.
You are likely to be highly self-motivated with a passion for applying emerging technologies in a real-world environment - the type of person who is motivated to explore new approaches that add value to data sets.
You’ll work in a non-bureaucratic environment, where you will be trusted, supported to deliver results and comfortable being accountable for progress.
You are likely to be
a technology/ software enthusiast, keen to learn, researching new technologies / tools and an “evangelist” for machine learning and data analytics
an Engineering or Computer Science graduate.
experienced with embedded software development, C, C++, Python.
understand how to interface software from external vendors
demonstrable interest in big data, data analytics and learning based approaches.
familiar with engineering applications
able to communicate and explain complex processes to non-specialists
Suitable for people from fresh graduate up to a mid-level engineer, the skills listed above are wish-list, the more relevant activities that you can demonstrate you have done in a 'real-world' environment the better.