Lead Data Scientist – Causal AI

  • Full Time
  • London
  • Posted 6 months ago

causaLens

Job title:

Lead Information Scientist – Causal AI

Firm

causaLens

Job description

causaLens is the pioneer of Causal AI — an enormous leap in machine intelligence.We’re on a mission to construct actually clever machines, machines that actually perceive trigger and impact— it’s laborious however tremendous enjoyable! If you wish to construct the longer term and are on the lookout for a spot that values your curiosity and ambition, then causaLens is the proper place for you. Every little thing we do is on the forefront of technological developments, and we’re all the time looking out for individuals to hitch us whose expertise and keenness tower above the remainder.For the reason that firm was established in 2017, causaLens has:
🥳Launched decisionOS, the primary and solely enterprise resolution making platform powered by Causal AI –🚀Open sourced two of our inner instruments and packages to assist the open-source neighborhood, see and .🦄Raised $45 million in Collection A funding
🏆Been named a number one supplier of Causal AI options by Gartner – 🚀Included in Otta’s 2022 Rocket Checklist as one of many fastest-growing firms to launch your professionAt causaLens we’re constructing the world’s most superior Causal AI powered resolution intelligence platform for Information Scientists. The platform leverages cutting-edge Causal AI algorithms and fashions to empower knowledge scientists and decision-makers to transcend correlation-based predictions and have an actual affect on crucial choices for the enterprise. Our platform is trusted and utilized by knowledge science groups in main organizations and gives actual worth throughout all kinds of industries, and it is solely the start.Our MissionTo radically advance human decision-making.A world during which people leverage reliable AI to unravel the best challenges within the financial system, society and healthcare.
Head to our and watch the ‘Why Causal AI’ video to be taught extra.The PositionWe’re on the lookout for a Lead Information Scientist based mostly in London to hitch us in spreading our Causal AI know-how to each enterprise on the planet. It is a full-time placement with vital alternatives for private growth. The Lead Information Scientist will handle a few of most essential deployments and engagements with the largest firms in each trade. Additionally, you will be tasked with growing causal-AI-driven fashions and resolution functions utilizing our know-how to unravel essentially the most high-impact challenges in industries like retail, advertising, provide chain, manufacturing and finance.What you’ll doAs a Lead Information Scientist at causaLens, you’ll play a pivotal position in advancing our Causal AI know-how. This place calls for a robust basis in knowledge science, notably with time sequence or tabular use-cases, ideally utilizing Python, and expertise managing knowledge science engagements with international Enterprises. A few of your tasks will embody:Stakeholder and challenge administration.Accountability for the profitable deployment of the causal AI platform, with a give attention to including worth and renewing every buyer.Utilizing our causal AI framework to construct causal fashions and resolution functions, utilizing our proprietary causal discovery, modelling, and resolution intelligence architectures on client-supplied knowledge units and use circumstances.Collaborating instantly with enterprise stakeholders to combine area information into the modeling course of, demonstrating how insights can improve resolution workflows.Crafting long-term visions and plans, in collaboration with purchasers and causaLens stakeholders, to efficiently implement causal fashions and insights into clients’ methods.Work carefully with the product and analysis groups to form the event of our platform.No less than 4 years of business knowledge science expertise with time sequence or tabular use-cases, ideally utilizing Python2 years expertise being liable for the profitable deployment of knowledge science initiativesSturdy educational file in a quantitative subject (MEng, MSci, EngD or PhD)Glorious and confirmed communication and teamwork expertiseEarlier expertise in excessive progress know-how firms or technical consultancy is a plusEarlier expertise in gross sales, pre-sales, and/or different technical evangelism is a plusExpertise in provide chain, demand forecasting, retail/cpg, manufacturing, advertising, monetary providers, or public sector is a plusAbout causaLens
Present machine studying approaches have extreme limitations when utilized to real-world enterprise issues and fail to unlock the true potential of AI for the enterprise. causaLens is pioneering Causal AI, a brand new class of clever machines that perceive trigger and impact — a serious step in direction of true synthetic intelligence. Our enterprise platform goes past predictions and gives causal insights and instructed actions that instantly enhance enterprise outcomes for main companies in asset administration, banking, insurance coverage, logistics, retail, utilities, power, telecommunications, and lots of others.We could also be biased, however we consider you’ll be in good firm. We provide a hybrid working setup and are devoted to constructing an inclusive tradition the place numerous individuals and views are welcomed. Apart from becoming a member of a sensible and provoking crew, you’ll be amongst people who find themselves all the time there to assist your concepts and encourage you to develop. We have fun our variations and are available collectively to share our triumphs!What we provide
We care about our individuals’s lives, each inside and outdoors of causaLens. Past the core advantages like aggressive remuneration, pension scheme, paid vacation, and a superb work-life stability, we provide the next:Entry to psychological well being assist by means of SpillAggressive wage25 days of paid vacation, plus financial institution holidaysShare choicesPension schemePleased hours and crew outingsReferral bonus programCycle to work schemePleasant tech purchasesWorkplace snacks and drinksLogisticsOur interview course of consists of some screening interviews and a “Day 0” which is spent with the crew (in-office). We’ll all the time be as clear as potential so please don’t hesitate to succeed in out you probably have any questions.

Anticipated wage

Location

London

Job date

Fri, 05 Apr 2024 01:05:07 GMT

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