Quantitative Analyst

Job description

Summary 

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. 

The Company 


causaLens leads causal AI research. Causality is a major step towards developing true AI. Our technology transforms organisations by autonomously discovering valuable insights that optimise business outcomes. Our flagship product, time-series prediction engine, goes beyond both traditional machine learning and AutoML. It has become the industry standard in the financial sector and is increasingly being used in a wide range of industries. causaLens is run by top scientists and engineers, 70% holding a PhD in a quantitative field. For more information visit www.causaLens.com or contact us on info@causaLens.com. Follow us on LinkedIn and Twitter.


causaLens in the News

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. 


Benefits


  • The opportunity to join a fast-growing, agile, and international team passionate about innovation and making a difference
  • Competitive remuneration
  • Share option scheme
  • Pension scheme
  • 32 days paid holiday allowance (incl. bank holidays)
  • Equipment you need to get the job done (MacBook Pro etc.)
  • Good work-life balance
  • Opportunities for continued learning and self-development, including courses, conferences and book budget
  • Flexible work-from-home and remote days
  • Cycle to work scheme
  • Weekly journal club and knowledge sharing presentations
  • Regular team outings, pizza Thursdays and annual company retreats
  • Fruits, snacks and soft drinks in the office
  • Amazing, smart, fun and inspiring colleagues, always there to support your ideas, growth and enthusiasm

Logistics

Our interview process consists of an intelligence test, interview and an on-site visit. We will do our best to transparently communicate the process with the successful candidates.

Job requirements

Core requirements: 

● Experience building predictive models 

● Ability to translate advanced machine learning algorithms into code (Python preferred)

● 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)