Data Scientist – Revenue Optimisation Manager

Job title:

Data Scientist – Revenue Optimisation Manager

Company

University of Birmingham

Job description

Salary: Full time starting salary is normally in the range £35,880 to £45,163 with potential progression once in post to £47,874Role SummaryThe Lapworth Museum of Geology seeking to appoint a specialist Data Scientist- Revenue Optimisation Manager (DS-ROM) to play a pivotal role in its strategic development and management. The (DS-ROM) will provide high-level management support and work closely with the Museum Director to shape the Museum’s strategic direction.The role involves utilising advanced data modelling to increase revenue through the museum’s retail offerings, innovative venue hire, paid events programs, and the development of a commercial image library.The DS-ROM will utilise specialist skills in data science, AI, and machine learning to lead data-driven initiatives that support research, teaching, public engagement, and financial growth. Key responsibilities include implementing cutting-edge AI solutions, management of the full data cycle (collection, storage, processing, analysis, visualization, utilisation, and security), to inform the development of major public events programmes, and driving revenue generation. The role includes managing the Visitor Services team, reception, and retail outlet through data driven initiatives to ensure high-performance operations while contributing to the museum’s strategic planning and reporting.The Lapworth is an integral part of the School of Geography, Earth and Environmental Sciences (GEES) within the College of Life & Environmental Sciences at the University of Birmingham and provides considerable support for teaching and research within the school, and college. The post-holder will assist the Director to ensure that teaching and research links between the Lapworth, GEES, other academic schools and wider Higher Education community are maintained and developed.

Person SpecificationApplicants should have a relevant qualification at degree level in a quantitative field (preferably Maths & Statistics) and a Masters degree in Artificial Intelligence & Machine Learning. They should have experience of applying Data Science, Artificial Intelligence & Machine Learning in a similar museum, research and teaching environment.Informal enquiries can be made to Jon Clatworthy (Museum Director), email:To download the full job description and details of this position and submit an electronic application online please click on the ‘Apply’ button above.Valuing excellence, sustaining investment
We value diversity and inclusion at the University of Birmingham and welcome applications from all sections of the community and are open to discussions around all forms of flexible working.Closes: 25/11/2024£35,880 to £45,163. Grade 7

Expected salary

£35880 – 45163 per year

Location

Birmingham

Job date

Wed, 20 Nov 2024 01:16:11 GMT

To help us track our recruitment effort, please indicate in your email/cover letter where (hiring-jobs.com) you saw this job posting.

Share

HIRING NOW- OTR DRIVERS WANTED

Job title: HIRING NOW- OTR DRIVERS WANTED Company DriveLine Solutions Job description HIRING NOW- OTR…

5 minutes ago

Remote Customer Sucess Team Lead-SD

Job title: Remote Customer Sucess Team Lead-SD Company AO GLOBE LIFE Job description is an…

18 minutes ago

Soft Tissue Trainee Programme

Job title: Soft Tissue Trainee Programme Company Brentford Football Club Job description Job Title: Soft…

19 minutes ago

Childcare Teacher (Hiring Bonus)

Job title: Childcare Teacher (Hiring Bonus) Company The Sunshine House Job description Childcare Teachers |…

29 minutes ago

Sales Executive – Toyota. Existing or Career Change (Letchworth) – 19236

Job title: Sales Executive – Toyota. Existing or Career Change (Letchworth) – 19236 Company Steven…

38 minutes ago

Searching For a Reliable Housekeeper

Job title: Searching For a Reliable Housekeeper Company Job description We are looking for someone…

47 minutes ago
For Apply Button. Please use Non-Amp Version

This website uses cookies.