About us

What we stand for

vision = global_economy.predict().optimize()


causaLens is pioneering a completely new approach to time-series prediction. Its Enterprise Platform is used to transform and optimise businesses that need accurate and robust predictions – including significant businesses in finance, IoT, energy and telecoms. Almost all current machine learning approaches, including AutoML solutions, severely overfit on time-series problems and therefore fail to unlock the true potential of AI for the enterprise. causaLens was founded with the mission to devise Causal AI, which does not overfit, and so provides far more reliable and accurate predictions.  The platform also includes capabilities such as autonomous data cleaning and searching, autonomous model discovery and end-to-end streaming productisation. 

 

causaLens is on a mission to build truly intelligent machines that go beyond current machine learning approaches - a curve-fitting exercise. Devising Causal AI has allowed us to teach machines cause and effect for the first time - a major step towards true AI. 

 

causaLens is run by scientists and engineers, the majority 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.

Our values and principles are to be: 

  • Kind and Inspirational
  • Trustworthy and Accountable  
  • Driven and Resilient


Now recruiting for multiple positions in Data Science, Python Eng, Front End Dev, Commercial roles and more


causaLens.optimize (employee_happiness, positive_impact_on_the_world, share_price)


Our vision is to optimize the global economy

Dr. Darko Matovski
CEO, causaLens

Perks & Benefits

A selection of what we have to offer

  • Innovative & dynamic environment
  • Deep-tech company experience
  • Turbo charged growth
  • Guidance and mentorship
  • Smartest teammates
  • Competitive salary
  • 32 days paid holiday allowance (incl bank holidays)
  • Equity / Share options
  • Pension scheme
  • Work from home days
  • Happy hours and team outings
  • Remote work possibilities
  • MacBook Pro workstations
  • Referral bonus program
  • Conference allowance
  • Library allowance
  • Cultural and sports allowance
  • Cycle to work scheme
  • Friendly tech purchases
  • Pizza Thursdays
  • Healthy snacks and drinks in the office
  • Casual dress code
  • causaLens swag

Videos

What we do and who we are from the words of our founders

causaLens in the news

⦁ Best Deeptech Company 2019 - Artificial Intelligence Awards
⦁ ‘Meet causaLens, a Predictive AI For Hedge Funds, Banks, Tech Companies’ – Yahoo Finance 
⦁ ‘The U.K.’s Most Exciting AI Startups Race To Scale’ - Forbes
⦁ ‘Auto ML Platform Draws Interest from Discretionary Funds’ - machineByte
⦁ ‘AllianzGI Taps Virtual Data Scientists amid War for Talent’ - Financial Times
⦁ ‘Machine Learning Companies to watch in Europe’ - Forbes
⦁ ‘Best Investment in Deeptech’ award - UK Business Angels Association awards
⦁ ‘100 Most Disruptive UK Companies’ - Hotwire
⦁ ‘causaLens Appoints Hedge Fund Veteran and Data Leaders to Advisory Board’ - Newswire

Join us

Current openings

Director of New Products
Product
Talent Acquisition & Operations Associate
Human Resources
Data Scientist - Innovative Applications of Causal AI
Marketing
Director of Account Management - Causal AI
Sales
Director of Strategic Sales
Sales
Data Science - Machine Learning Research
Causality & Blue Sky Research
Director of ML Engineering
Product
Director of Causality and Blue Sky Research
Causality & Blue Sky Research
Data Scientist – Causality Expert
Causality & Blue Sky Research
Data Scientist - Reinforcement Learning
Causality & Blue Sky Research
Director of Applied Data Science - Financial Services
Applied Data Science
Director of Sales - Financial Services
Sales
Scientific Researcher & Writer
Marketing
Frontend Engineer
Product
Data Scientist - Applied Science
Applied Data Science
Data Scientist - Engineering and Product
Product
Software Engineer
Product
Business Problem Solver (Jared)
Growth
Quantitative Researcher
Applied Data Science