Full-Time Manager – Quantitative Analytics @ London, United Kingdom
The Data Intelligence & Analytics team at Investigo are currently looking to recruit a Manager – Quantitative Analytics on behalf of our client, a global financial services and insurance company. This role would be part of the Data Science team – a specially formed unit looking at the power of technology, data and computational science aiming to transform how business is done in the industry. The Science team is responsible for data engineering for the entire global group. The role will be based in Central London.
The ideal candidate will have experience in:
- Integration of machine learning with big-data and/or high-performance computing platforms (e.g., Spark, Hadoop and CUDA)
- Integration of machine learning with front-end systems (e.g., native mobile apps and HTML5+JS front-end systems)
- Employing machine learning in a collaborative commercial settings (using DevOps methodologies and tools such as GitHub)
- Publication in the top scientific journals and conferences
- Leading scientific projects
Success in this role requires the candidate to:
- Employ the existing (and develop new) machine-learning algorithmsthat can find patterns in large multi-modal data.
- Innovate and provide solutions (e.g., by translating complex commercial problems to machine learning problems).
- Be an active member of teams that provide the business with data-driven apps, insights and strategies.
- Participate in, lead, and create cross-functional projects and trainings.
- Communicate (both oral and written) with colleagues and stakeholders (both internal and external).
- Review, direct, guide, inspire the research of more junior scientists in the team
Candidates must have:
Scientific expertise and applied experience in machine learning (ideally, a combination of excellent academic research and high-impact commercial experience)
- Education Preferred – PhD (or equivalent)
- 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 techniques (e.g.,classification, regression and clustering)
- Track record in advanced topics of machine learning (e.g., Bayesian inference, hierarchical models, deep learning, Gaussian processes, causal inference, …)
- Advanced programming skills in Python and R (and their related data processing, machine learning, and visualisation libraries)
- Practical experience in preparing data for machine learning (e.g., using SQL and/or NoSQL technologies)
- Excellent communication skills