Job Description
GamCare is the UK’s leading provider of information, advice, and support for anyone affected by gambling-related harms. GamCare work across the UK and deliver support and treatment both directly and through a network of locally based partners.
Role
As a result of this we are currently looking for the following role to join the organisationIt is an exciting time to join us. As the sector evolves, we too are rapidly developing new ways of working to extend our reach and impact. This has included new programmes of work, as well as new ways of doing things.The Data Scientist will support the strategic planning and insight functions within GamCare and be responsible for integrating and structuring management information across the business. The post holder is responsible for the delivery of data modelling across all business needs and wider research purposes. They will support the delivery of an evidence-based approach to identifying, recognising, and understanding future challenges, ensuring the entire organisation is aligned to delivering our purpose and values.
Role Responsibility
- Generating large databases from various sources of structured and unstructured data
- Analysing data and generating statistical information to identify trends and patterns
- Understanding the phases of product delivery and expert analyses across product life cycles, running the analysis for each stage and contributing to decision making.
- Translating technical data to simple language and giving recommendations and conclusions to stakeholders
- Develop interactive dashboards that combine visuals with real time data
- Building scalable machine learning pipelines and using feature engineering and optimization methods to improve data set performance
- Combine models through ensemble modelling
The Ideal Candidate
As the successful candidate you’ll be working as part of the Quality and Innovation Directorate who are responsible for Governance, Data and Business insights. You will have experience in in building predictive models and machine-learning algorithms alongside supporting the development of manuals and training materials that support improved data literacy across the business. You will have experience using business intelligence tools Power BI and Tableau as well as knowledge of SQL, Azure and Python and / or R.The post offers an excellent opportunity to work in a forward-thinking team environment and make a difference to the service user experience and recovery. This role is a new role within GamCare and as such there is room for growth and the right candidate to make this role their own.
Package Description
Data ScientistPermanent, Full time 35 hoursSalary: London and Surrounding counties, £43,734. Rest of UK based, £40,301Work from home with bi-weekly travel into London office for one dayClosing date for applications: 16.07.23
Interviews will take place online via video conference – TBC
- 33 days basic annual leave entitlement per annum (pro-rated for part-time colleagues) including bank holidays which increases with service
- A generous Pension Scheme – we contribute 6% and you contribute 2%.
- Discretionary company sick pay from day one of service.
- Employee Assistance Programme – 24-hour support
About the Company
GamCare are committed to offering the best support to people affected by gambling harms, as such we welcome applications from candidates with lived experience.
Gamcare is an equal opportunities employer and don’t discriminate based on race, religion, gender, age, sexuality, gender identification, or physical ability. We are only able to facilitate visa sponsorship in very limited circumstances, so candidates outside of the UK or who don’t have the right to work in the UK need not apply.For any further information on the role or if you require any reasonable adjustments at any stage of the application or recruitment process, please contact recruitment@gamcare.org.uk and the team will be happy to help.
More Information
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1