My client who are a Global Insurer baesd in the City of London are currently recruiting for a Machine Learning AI Scientist based.
Perm - £100/£150K - London - Data AI Scientist
You require the following:
Both senior candidates (i.e., with years of post-doctoral and/or industrial experience) and junior candidates (i.e., recent PhD graduates) are welcome to apply; we have and will offer positions appropriate to expertise and level of experience.
The minimum required skills include:
- A postgraduate (MSc/PhD/Post-doc) qualification in a numeric discipline such as Statistics, Machine Learning, Computer Science, Signal Processing etc.
- Scientific expertise and applied experience in Machine Learning (ideally, a combination of excellent academic research and high-impact commercial experience).
- In depth understanding of common Machine Learning algorithms (e.g., for classification, regression and clustering).
- In depth knowledge of advanced statistical theories, methodologies, and inference tools (e.g. familiar with hypothesis testing, (generalized) linear models, additive models, mixture models, non-parametric models, etc.).
- Proven track record in advanced topics of Machine Learning (e.g., Bayesian inference, hierarchical models, deep learning, Gaussian processes, causal inference, graph theory, etc.).
- Advanced programming skills in Python and R (and their related data processing, Machine Learning, and visualization libraries).
- Practical experience in preparing data for Machine Learning (e.g., using SQL and/or NoSQL technologies).
- Completion of at least one significant project (equivalent of a great PhD research project, and/or a viable commercial product) in applied Machine Learning.
- Excellent communication skills
An ideal candidate (is not required to, but) will also have:
- Integration of Machine Learning algorithms with big-data platforms (e.g., Spark) and high-performance computing ecosystems (e.g., CUDA).
- Programming in C++, Java.
- Deployment of algorithms as real time/ highly available services.
- Integration with front-end systems (e.g., HTML5/ native mobile apps).
- Employing Machine Learning in collaborative commercial settings (e.g., using DevOps methodologies and tools such as GitHub), ideally, in collaboration with product development teams.
- Leading scientific projects.
- Publication record in top scientific journals and conferences such as NIPS, ICML, ICLR, and AAAI etc.)
- Senior candidates should have proven ability to engage with business, formulate technical problems from business needs and craft solutions to shape business priorities