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Research Scientist - Machine Learning and Causality at causaLens

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  • London
  • fulltime
  • -
  • Summary

    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.

     

    The Company

    Current machine learning approaches have severe limitations when applied to real-world business problems and fail to unlock the true potential of AI for the enterprise. causaLens is pioneering Causal AI, a new category of intelligent machines that understand cause and effect - a major step towards true artificial intelligence. Our enterprise platform goes beyond predictions and provides causal insights and suggested actions that directly improve business outcomes for leading businesses in asset management, banking, insurance, logistics, retail, utilities, energy, telecommunications and many others.

     

    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

     

     

    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 a couple of online interviews and an on-site visit. We will do our best to transparently communicate the process with the successful candidates.

    Job requirements

    • 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

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