Hydrogen Group are currently looking to recruit a permanent Data & Analytics Manager to join a large financial organisation. The successful candidate can be based in any of the following locations - Edinburgh, Manchester, Bristol, Belfast or London.
The company work a hybrid model with the expectation of the successful candidate working 3 days from home and 2 days in the office. This is an opportunity to take on a purpose-led leadership role in a cutting-edge Data & Analytics team. The salary is competitive with an excellent benefits package.
What you'll do
As a Data & Analytics Manager, the successful candidate will be leading and coaching colleagues to plan and deliver strategic agreed project and scrum outcomes. The successful candidate will drive the use of advanced analytics in their team to develop business solutions which meet the needs of our stakeholders and increase the understanding of our business, including its customers, processes, channels and products.
- Working closely with business stakeholders to define detailed, often complex and ambiguous business questions, problems or opportunities
- Planning and delivering data and analytics resource, expertise and solutions, which brings commercial and customer value to business challenges
- Communicating data and analytics opportunities and bringing them to life in a way that business stakeholders can understand and engage with
- Adopting and embedding new tools, technologies and methodologies to carry out advanced analytics
- Developing strong stakeholder relationships to bring together advanced analytics, data science and data engineering work that is easily understandable and links back clearly to our business needs
Hydrogen Group are looking for a capable leader with a passion for data and analytics, and experience of coaching and supporting their colleagues to succeed. Along with advanced analytics knowledge, you'll bring an ability to simplify data into clear data visualisations and compelling insight using appropriate systems and tooling.
· Knowledge of data architecture, key tooling and relevant coding languages
· Strong knowledge of data management practices and principles
· Experience of translating data and insights for key stakeholders
· Good knowledge of data engineering, data science and decisioning disciplines