causaLens is a rapidly growing business that is pioneering a new category of intelligent machines that understand cause and effect - this goes beyond predictions and provides causal insights and suggested actions that directly improve business outcomes for our clients. Our technology has applicability across a whole range of sectors including banking, asset management, insurance, logistics, retail, utilities, energy, and telecommunications.
As we continue to expand our business, we are looking for a motivated and high-achieving Research Scientist in Machine Learning and Causality to join our Research team based in London on our vision to optimise every business on the planet. This is a full-time placement with significant opportunities for personal development.
We offer an intellectually stimulating environment, work within an interdisciplinary team and an inclusive culture. We are a high-calibre, mission-driven team building a technology that improves our world. We are committed to diversity and are committed to ensuring that everyone feels at home and can contribute as a peer within the business.
Roles and Responsibilities
This is an exciting role for a smart, creative person to focus on research topics in Machine Learning and to extend the cutting edge of Causality. The successful candidate will join the CLX research group focusing on Causality & Blue Sky Research.
We are committed to addressing the diversity problem in the tech industry, and that starts with making sure we have a team where everyone feels at home and can contribute as a peer.
causaLens in the News
Our interview process consists of a couple of online interviews and an on-site visit. We will do our best to transparently communicate the process with the successful candidates.
PhD in a quantitative field (machine learning / computer science / statistics / physics / mathematics, or comparable)
Research or Industrial experience in Machine Learning, Deep Learning or Reinforcement Learning is necessary
Research or Industrial experience in causality (e.g. causal inference and causal discovery) is a plus
Creativity and ability to come up with ideas to tackle very hard problems and design/implement cutting edge solutions
Ability to translate advanced machine learning algorithms into code (Python preferred)
Smart, capable and can write clean code effectively
Knowledge of the software development lifecycle (version control, tooling, testing, etc.)
Highly capable, self-motivated, collaborative and personable
Ability to demonstrate integrity and drive
Naturally curious and effective problem solver
An excellent written and verbal communicator with a high level of business acumen
Ability to effectively work independently in a fast-moving environment