We are looking for a motivated and high-achieving Quantitative Analyst based in London to join the team working on our exciting Machine Learning product. 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 on a mission to develop a machine that predicts the global economy in real-time. Our technology helps organisations plan and optimise business outcomes, thus improving efficiency and protecting the environment.
- causaLens in the 100 most disruptive UK companies
- causaLens in the Forbes 'Top 15 Machine Learning Companies to watch in Europe'
Roles and Responsibilities:
This is an exciting role for a smart, creative person to build sophisticated predictive models on time-series data using the causaLens platform.
The successful candidate will have:
The opportunity to join a fast-growing, agile, and international team passionate about innovation and making a difference
Access to guidance, mentorship, and opportunities for turbo-charged professional development
An employee share option scheme
A pension scheme
32 days paid holiday allowance (incl bank holidays)
Equipment you need to get the job done (MacBook Pro etc.)
Opportunities for continued learning and self-development, including courses and book budget
Opportunity to publish work and patents
Cycle to work scheme
Regular team outings, pizza Thursdays and annual company retreats
Fruits, snacks and drinks in the office
Amazing, fun and inspiring colleagues, always there to support your ideas, growth and enthusiasm. We are an international team passionate about innovation and making a difference
Our interview process consists of a test, intro interview and one on-site visit. We will do our best to transparently communicate the process with the successful candidates.
● Experience building predictive models
● Highly capable, self-motivated, collaborative and personable
● Strong academic record
● Interest in advanced technologies such as machine learning
● 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 and remotely (from home or coworking space)