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Applied Data Scientist

causaLens
10 months ago
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Applied Data Scientist

Senior Data Scientist: Build & Deploy ML/AI Solutions

Senior Data Scientist

Applied Data Scientists

Data Scientist

Senior Applied Data Scientist

causaLens is pioneering the world’s first platform for building AI data scientists - empowering everyone to create and deploy their own data science agents in days. Our platform enables teams to collaborate in a multi-agent environment, ensuring human oversight across the entire workflow and making AI-powered data science trustworthy and accessible to everyone – from analysts to business leaders. We power industry leaders, including Cisco, Johnson & Johnson, Canon, and McCann Worldgroup, to accelerate and scale their data science capability. Join us to build the World’s First Platform for AI Data Scientists.What we are looking forWe are looking for a Senior Data Scientist based in London to join our mission to create AI Data Scientists to radically advance decision-making for leading enterprises. You will join a team of 9 Data Scientists. We hire the top 1% of Data Science talent to create an intellectually stimulating environment where you can thrive and learn. You will be helping leading enterprises build their custom data science agents and help our users get the maximum out of the platform. What you will doAs a Senior Data Scientist at causaLens, you will play a pivotal role in advancing our decision-making technology. This position demands a strong foundation in data science, particularly but not limited to time series, and using Python as the primary programming language. Some of your responsibilities will include:Using our Agentic AI framework to build data science solutions and models, using our platform on client-supplied data sets and use cases.Collaborating directly with business stakeholders to integrate domain knowledge into the modelling process, demonstrating how insights can enhance decision workflows.Crafting long-term visions and plans, in collaboration with clients and causaLens stakeholders, to successfully deploy agentic workflows into customers' strategies.Work closely with the product and engineering teams to shape the development of our platform.Communicate technical topics to non-technical audiences.RequirementsAt least 2 years of commercial data science experience using PythonPlease note that this and the following bullet imply a significant breadth and depth of technical skills we will be testing for during the interview process - e.G., Statistics; other programming/scripting languages; solid understanding andexperience with Cloud technologies; OOP, TDD, GitHub/Actions/Flow, and MLOps best practices; classical ML algorithms; at least some NLP, etc. Strong academic record in a quantitative field (MEng, MSci, EngD or PhD)Excellent and proven communication and teamwork skillsPrevious experience in high-growth technology companies or technical consultancy is a plusPrevious experience in sales, pre-sales, and/or other technical evangelism is a plusExperience with consulting and/or customer-facing roles, especially in the supply chain, demand forecasting, retail/cpg, manufacturing, marketing, financial services, or the public sector is a plusExperience with LLM and RAG, GenAI, and agentic workflows is a plusBenefitsWe care about our people’s lives, both inside and outside of causaLens. Beyond the core benefits like competitive remuneration, and a good work-life balance, we offer the following:25 days of paid holiday, plus bank holidaysbuy/sell holiday options (up to 5 days)Share optionsPension schemeHappy hours and team outingsReferral bonus programCycle to work schemeFriendly tech purchasesBenefits to choose from include Health/Dental InsuranceSpecial DiscountsLearning and development budgetWork abroad daysOffice snacks and drinksLogisticsOur interview process consists of a few screening interviews and a "Day 0" which is spent with the team (in-office). We will always be as transparent as possible so please don’t hesitate to reach out if you have any questions.If you require accommodations during the application process or in your role at causaLens, please contact us at

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