Data Scientist - Innovative Applications of Causal AI

Job description

Summary

We are looking for a motivated and high-achieving Data Scientist based in London to join the team 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.


Roles and Responsibilities

This is an exciting role for an intelligent, forward thinking, creative person with a strong technical background and desire to apply their skills in a stimulating commercial environment. Your work will include:
• Researching and developing novel use-cases for the causaLens technology
• Generating new ideas for the application of causal AI throughout a range of industries
• Communicating these ideas with the community through blogs & social media
• Building models to prove the value of our technology and facilitate its adoption
• Inspiring new customers about the importance of causal AI in business applications


    The Company

    causaLens is pioneering Causal AI, a new category of intelligent machines that understand cause and effect - a major step towards true AI. Its enterprise platform is used to transform leading businesses in Finance, IoT, Energy, Telecommunications and others.


    Current machine learning approaches, including AutoML solutions, have severe limitations when applied to real world business problems and fail to unlock the true potential of AI for the enterprise. For instance, in the case of predictions, they severely overfit and do not adapt when the environment changes. causaLens’ Causal AI Platform goes beyond predictions, providing transparent causal insights and suggesting actions that directly improve business KPIs.


    causaLens is run by scientists and engineers, the majority holding a PhD in a quantitative field. Contact us on info@causaLens.com or follow us on LinkedIn and Twitter.


    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 challenge, screening interviews and a "Day 0" which is spent with the team. Normally the Day 0 takes place on-site but for the time being, they will take place online. We will do our best to transparently communicate the process with successful candidates.

    Job requirements

    • Strong academic record (MEng, MSci, EngD or PhD)
    • High creativity
    • Ability to discover the business potential of novel technologies
    • Advanced quantitative skills in machine learning/statistics/mathematics or similar fields
    • Ability to apply complex technologies in novel high-value use-cases
    • An excellent written and verbal communicator with a high level of business acumen
    • Highly capable, self-motivated, collaborative and personable
    • High integrity and drive
    • Understanding of financial markets is preferable
    • Naturally curious and effective problem solver
    • Ability to effectively work independently in a fast-moving environment
    • Strong coding skills, preferably in Python