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Data scientist apprenticeship

Two young bp colleagues walking and talking

Global Business Services (GBS)

 

Study for a Level 6 BSc (Hons) digital & technology solutions

The digital & technology solutions professional apprenticeship is suitable for aspiring tech professionals looking to build their career innovating and delivering impact through technology. The programme enables the development of well-rounded, business-ready digital talent.

 

The business process management and process mining centre of expertise is hosted by Global Business Services (GBS) and operates as a shared service providing business process management and process mining capability across the group. The process mining CoE manages the process mining toolset, data models and analytics to support across GBS processes and group to provide visibility of our executed processes and identify and support improvement initiatives. 

 

Each data model developer apprentice will be tagged to a lead DM developer who will be tasked with the creation and maintenance of data models for the group of projects assisted to them, the apprentice will assist and support the lead developer. They will as a team finding and understanding source data from ERP systems, taking source data tables and translating this through coding into a step-by-step process output. The role will work within an agile based project environment for initial and large data model development and as part of a continuous improvement, BAU type environment. The process scope for each data model developer will cut across any process, however will primarily be supporting S2P, O2C or R2R. 

 

This is an exciting new space for bp and GBS specifically and the successful applicant will have the opportunity to develop the capability within the group and support the growth of the team while studying and developing their skill set in data science.

What to expect

  • Assisting the DM development lead to translate complex functional and technical requirements into data models, supporting the coding and build of these data models, making changes where required and building new content
  • Assisting and in some projects leading the setup of process data extractions including table and field mappings, liaising with the IT&S team to ensure time lines are met and the data is transferred in a timely complete manner
  • Testing of data connections and data validation
  • Assisting with the process mining system maintenance and upgrade management
  • Working with IT&S to ensure integrity of hardware and software, including backups and data management
  • Setup of process data extractions including table and field mappings
  • Dealing with system access management
  • Assisting with the design of KPI’s and metrics, through dashboard building and analytics

 

Key challenges

 

  • As the scope is cross group and cross process, the role demands the ability to quickly grasp a varied scope and work within a deliver focused agile environment
  • Building expertise within the process mining and ETL activities
  • Assisting the DM development lead to translating multiple and complex requirements (use cases) into data models that represent the internal customers desired outputs
  • A keen interest in data analytics and data science is a key requirement to bring new thinking to the team and this area

Essential experience and job requirements

  • Strong interpersonal relationship building skills
  • Good planning and organising skills 
  • Excellent team worker
  • Ability to capture and share best practice
  • Desire to improve their skills as a data scientist and continue study and on the job leaning
  • Inquisitive
  • Desire to challenge others

 

To apply, you must be aged 21 or over at start of the programme in September 2023. 

Essential education

  • STEM degree qualified or equivalent qualification

Any travel required as part of your apprenticeship will be up to 20%. We’re happy to discuss any reasonable adjustments you may require.

 

The opportunity will be based at our offices either in London or Budapest.