Lead Data Scientist

3 weeks ago

Hammersmith, United Kingdom causaLens Full time

causaLens is the pioneer of Causal AI — a giant leap in machine intelligence.


Increase your chances of reaching the interview stage by reading the complete job description and applying promptly.

We are on a mission to build truly intelligent machines, machines that truly understand cause and effect— it’s hard but super fun If you want to build the future and are looking for a place that values your curiosity and ambition, then causaLens is the right place for you. Everything we do is at the forefront of technological advancements, and we are always on the lookout for people to join us whose skills and passion tower above the rest.

Since the company was established in 2017, causaLens has:

Launched decisionOS, the first and only enterprise decision making platform powered by Causal AI - here

Open sourced two of our internal tools and packages to support the open-source community, see Dara and Causal Graphs.

Raised $45 million in Series A funding

Been named a leading provider of Causal AI solutions by Gartner - here

Included in Otta’s 2022 Rocket List as one of the fastest-growing companies to launch your career

At causaLens we are building the world's most advanced Causal AI powered decision intelligence platform for Data Scientists. The platform leverages state of the art Causal AI algorithms and models to empower data scientists and decision-makers to go beyond correlation-based predictions and have a real impact on the most important decisions for the business. Our platform is trusted and used by data science teams in leading organizations and provides real value across a wide variety of industries, and it's only the beginning.

Our Mission

To radically advance human decision-making.

A world in which humans leverage trustworthy AI to solve the greatest challenges in the economy, society and healthcare.

Head to our website homepage and watch the ‘Why Causal AI’ video to learn more.

The Role

We are looking for a Lead Data Scientist based in London to join us in spreading our Causal AI technology to every business on the planet. This is a full-time placement with significant opportunities for personal development. The Lead Data Scientist will manage some of most important deployments and engagements with the biggest companies in every industry. You will also be tasked with developing causal-AI-driven models and decision applications using our technology to solve the most high-impact challenges in industries like retail, marketing, supply chain, manufacturing and finance.

What you will do

As a Lead Data Scientist at causaLens, you will play a pivotal role in advancing our Causal AI technology. This position demands a strong foundation in data science, particularly with time series or tabular use-cases, preferably using Python, and experience managing data science engagements with global Enterprises. Some of your responsibilities will include:

  • Stakeholder and project management. 
  • Responsibility for the successful deployment of the causal AI platform, with a focus on adding value and renewing each customer.
  • Using our causal AI framework to build causal models and decision applications, using our proprietary causal discovery, modelling, and decision intelligence architectures on client-supplied data sets and use cases.
  • Collaborating directly with business stakeholders to integrate domain knowledge into the modeling process, demonstrating how insights can enhance decision workflows.
  • Crafting long-term visions and plans, in collaboration with clients and causaLens stakeholders, to successfully implement causal models and insights into customers' strategies.
  • Work closely with the product and research teams to shape the development of our platform.

Job requirements

  • At least 4 years of commercial data science experience with time series or tabular use-cases, preferably using Python
  • 2 years experience being responsible for the successful deployment of data science projects
  • Strong academic record in a quantitative field (MEng, MSci, EngD or PhD)
  • Excellent and proven communication and teamwork skills
  • Previous experience in high growth technology companies or technical consultancy is a plus
  • Previous experience in sales, pre-sales, and/or other technical evangelism is a plus
  • Experience in supply chain, demand forecasting, retail/cpg, manufacturing, marketing, financial services, or public sector is a plus

About causaLens

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 may be biased, but we believe you’ll be in good company. We offer a hybrid working setup and are dedicated to building an inclusive culture where diverse people and perspectives are welcomed. Aside from joining a smart and inspiring team, you’ll be amongst people who are always there to support your ideas and encourage you to grow. We celebrate our differences and come together to share our triumphs

What we offer

We care about our people’s lives, both inside and outside of causaLens. Beyond the core benefits like competitive remuneration, pension scheme, paid holiday, and a good work-life balance, we offer the following:

  • Access to mental health support through Spill
  • Competitive salary
  • 25 days of paid holiday, plus bank holidays
  • Share options
  • Pension scheme
  • Happy hours and team outings
  • Referral bonus program
  • Cycle to work scheme
  • Friendly tech purchases
  • Office snacks and drinks

Logistics

Our 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.

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