Job Role: CAP-AI Data Science Advisor

Location: Central London


Capital Enterprise

Capital Enterprise is the membership organisation for providers of enterprise support services in London. Capital Enterprise’s prime mission is to support its members to individually and collectively acquire the means and expertise to better support their clients – London’s Entrepreneurs.


Our network of London’s leading universities, accelerators, co-working spaces, colleges, local authorities, enterprise support organisations, is a community of organisations committed to making London the best place in Europe to start and scale a business.


Capital Enterprise and its members provide a wide range of support services including advice, training, mentoring, accelerator programmes, specialist technical expertise, networking, soft loan finance and incubator accommodation to both pre-start and trading entrepreneurs and small businesses in all 33 London Boroughs.


We are a not-for profit organisation owned by, and run for the benefit of, members. Capital Enterprise is funded through members subscriptions, third party sponsorship and by income received from public/private sector partners to develop, pilot and manage innovative programmes that support enterprises and entrepreneurs in London.


CAP-AI  Programme Summary


The overall aim of the CAP-AI project is to help AI and Machine Learning SMEs to access the technical expertise, data and computation power, knowledge and innovation they need to survive and grow. There are 2 interlinked areas of activity:

  • Knowledge exchange brokerage to enable SMEs to tap into specialist AI and Machine Learning knowledge, research and talent coming out of London’s universities;
  • Innovation brokerage to enable SMEs to access high performance computing power through a Machine Learning Computation Lab and to engage in innovation activity bringing together corporates, industry, academics and SMEs.


Roles and Responsibilities

The key role of the Data Science Advisor is to assist London’s top AI first startups in scoping short-term and long-term Artificial Intelligence focused R&D projects for MSc/Post-Doc students to work with them on. The Data Science Advisor will work with each start-up to define the specific needs to the business in terms of their AI capabilities and then find and match the students to complete the projects.


In this role you will:


  • Source and engage with potential eligible AI Start-ups/Scale-ups throughout the duration of the CAP-AI programme.
  • Assess the eligibility of potential AI Start-ups/Scale-ups and their needs as a business to benefit from our support
  • Register eligible Start-ups/Scale-ups onto the programme and guide them through our support services
  • Working with eligible Start-ups/Scale-ups to scope 6-24month R&D projects, 12 week summer internships projects and long term collaboration projects with research institutions
  • Source and match CAP-AI companies with the most suitable candidate to fulfil their R&D project criteria
  • Maintain a relationship with all CAP-AI companies and their candidates throughout the R&D duration, giving expert advice and supervision
  • Achieve outputs set by the project
  • Monitor the delivery of the project and assess impact
  • Represent the CAP- AI project to the London AI community by attending and speaking at relevant Start-up and Academic/Student Events



  • 2+ years experience in supporting innovation focused businesses
  • Great knowledge about AI and Machine Learning
  • Exceptional presentation skills
  • Highly numerate and analytical
  • Exceptional and proven writing and communication skills
  • Take charge and deliver on your own; be proactive and independent
  • Knowledgeable and passionate about the Startup ecosystem




  • Previous Work in an AI company
  • Relevant Academic Qualifications
  • Knowledge of and contacts within the AI/ML student and alumni scene



Salary will be £43,000 pro rata, depending on experience

Salary will be paid in monthly instalments



Appointments are subject to receipt of satisfactory references and a probationary period of 9 months.


Hours of Work

Part-time hours average 21 hours per week



You will be entitled to 20 working days annual leave plus bank holidays pro rata, as well as additional time off between Christmas and New Year.


How to Apply

To apply for the vacancy send a CV and a cover letter to our HR Manager – Please note that any applications sent without a covering letter will not be successful.

Closing date for applications in Friday 18th January 2019.