Lead Data Scientist

Series-A Technology Start-Up

£80k - £100k plus equity, bonus & benefits

Hybrid / London Office 2 days per week

✅Support a portfolio of world-class clients in every industry

✅Innovative, collaborative culture, business driven by scientists & engineers

✅Inspiring leader, passionate about raising global awareness of AI

✅Chance to own shares in scaling organisation, collective drive towards exit

Join this market-leading Data Science and AI technology start-up as they continue to grow their Data Science team.

You will operate as part of a highly collaborative, innovative team to deliver data science solutions, under the leadership and guidance of an inspiring thought leader, in your Director of Data Science.

You will work across an extensive portfolio of global brands, in most key commercial industries, so the opportunity to diversify and develop your domain knowledge is huge.

You will deliver a variety of data science and AI projects and solutions, leveraging advanced mathematical and statistical programming and modelling skills including forecasting, time series and demand forecasting, to enable improved supply chain efficiencies, business performance and and questions around the customer.

You will also support the development of a proprietary AI platform, working closely with the developers and product teams.

Be part of this disruptive start-up as they continue to pioneer the use of machine learning and AI to drive enterprise value for end users.

Experience Required:

• Educated to at least master’s degree level in a relevant subject such as Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Physics, Chemistry, Engineering etc.
• Strong programming skills with Python, building algorithms and models, and working with large and complex data sets to extract insights.
• A background in applied data science within a commercial environment, comfortable with fast-paced, high growth culture.
• Ideally experience of working in a client or business facing environment, demonstrable skills in building trust and commercial discourse around leveraging ML and AI to solve real world business problems.
• Strong preference given to those with some form of scientific research experience, either during Phd or post-grad work experience.