Lecturer in Data Analytics
Ada, the National College of Digital Skills is a specialist college which inspires the students of today to become the digital pioneers of tomorrow. Our strong industry connections with industry leaders (Deloitte, Gamesys, IBM, King, Google) bridges the gap between education and the real world and ensures curriculum and programmes that fit with workplace and technical readiness. We believe all our students and staff should exhibit the following five values: Curiosity, Creativity, Resilience, Rigour and Collaboration.
In 2017, Ada launched its new Higher Level Apprenticeship in Digital Innovation, accredited by the Open University. At the end of the first two years of the programme, apprentices will gain a Foundation Degree in Digital Innovation, with progression opportunity to a full Bachelor Apprenticeship Degree. In addition to our established Degree Apprenticeship in Digital Innovation, we are about to launch a Higher Level Apprenticeship in Data Analytics & Visualisation.
We are seeking applications from individuals who can contribute directly to our new degree programme as lecturers in Data Analytics. The first year of the programme is delivered through an initial eight-week Launchpad, followed by week-long teaching, every six or seven weeks. For this role we are particularly seeking applicants who bring skills in statistical and automated data analysis using Python, data management, machine learning, database design and project planning. The role will undertake a variety of duties including, but not restricted to:
- Design, develop and deliver a range of modules within the programme of study across Levels 4 to 6 in a variety of settings from small tutorials to large lectures.
- Develop and apply appropriate teaching techniques and material which create interest, understanding and enthusiasm amongst students.
- Ensure that course design and delivery comply with the quality standards and regulations of the College.
- Setting and marking of assessments and provide constructive feedback to students.
- Seeking ways of improving performance by reflecting on teaching design and delivery and obtaining and analysing feedback.
- Lead and develop internal networks for example by participating in Institutional committee(s).
- Lead and develop external networks for example with external examiners.
- Develop links with external contacts such as employers and other educational bodies.
Successful candidates should have a Master degree qualification in a computing or related technical subjects, with a deep expertise in data analytics. Candidates with a Ph.D. are preferred. Applicants should have demonstrated excellent teaching in higher education or have presented regularly to technical audiences in an industry setting. Candidates should display a thirst for knowledge and academic learning in the context of real world challenges and a strong desire to see their theoretical work applied in solving impactful problems. The post is available as soon as possible and is based in London (Tottenham Hale/ Wood Green/ Whitechapel).
Variation to this Job Description This is a description of the job as it is at present, and is current at date of issue. The job description will be reviewed and updated as necessary to ensure that appropriate revisions are incorporated, and that it relates to the job to be performed. This process is carried out through discussions with Management. You are expected to participate fully in the review and, following discussion to update your job description as is considered necessary or desirable
The successful candidate will be required to apply for a Disclosure and Barring Service (DBS) check when appointed to the post. References for shortlisted candidates will be requested prior to the interview day. Further information about the DBS be found at www.gov.uk
How to apply for the role
Please submit a supporting cover letter and CV to firstname.lastname@example.org, in the subject field please write “Application for Lecturer in Data Analytics” followed by your name.
All appointments are subject to satisfactory references.