Data Scientist

Job description

Over the past ten years, Wood for Trees has improved the fundraising efficiency and value of some of the UK's best-known not-for-profit organisations, working with clients' data and database systems to make them better informed and more effective. In a wider context, we consult on strategic development, protecting and enhancing our clients' revenue streams for the future. We've built a reputation for providing valuable insight, strategic advice and pragmatic action that can have a significant effect on the bottom line. We are also expanding our analysis services and data science capabilities to support other areas of operational performance and assessment within the third sector such as impact reporting, digital transformation and management dashboards across the organisation.


We are in need of a Data Scientist to join our growing team. The ideal candidate will have an in depth understanding of data science techniques and their applications in a commercial setting. This is an opportunity for the successful candidate to take the next step in their career. They will become a part of a team that develops analytical tools, influences our product development and delivers insights to clients. We are looking for someone who:


  • Has experience using data science techniques to derive insights and create products.
  • Has strong communication and teamwork skills.
  • Can take ownership of projects from end-to-end. From investigating raw data, acquiring external data, making data pipelines and deploying models to production.
  • Has the confidence to challenge and communicate with senior stakeholders in the business.
  • Will work with all members of the team as well as directly with our clients
  • Is able to work in a fast-paced environment and understand the need for tight but simple processes to ensure work is executed quickly to meet project needs
  • Has the ability to identify new problems and prototype solutions while working closely with business experts to generate ideas and ensure adoption.
  • Can demonstrate the value of data science products and services to business stakeholders.

Job requirements

The Data Scientist will work with the Analysis Director, the Analysis team and the wider organisation to deliver internal and external data science projects. The work will require a combination of basic analytical methods as well as the latest data science techniques. The successful candidate will have a responsibility to ensure that work is delivered on time, within the scope and provide value for our clients. 


As a Wood for Trees Data Scientist, you will be empowered to develop, implement and support internal research and development. You will also need to deliver external projects and consultancy to our clients. Applying knowledge and experience, the successful candidate will build our AI/Data Science portfolio to support winning future work. As part of this varied role, you will also contribute to bid and proposal writing.


The successful candidate will have a love of problem-solving and be comfortable working collaboratively. They should have the confidence to build relationships with both internal teams and external customers, and the ability to communicate effectively with both technical and non-technical audiences


Skills and Experience 

  • A degree in mathematics, computer science, or other quantitative field.
  • Strong Data Science Programming skills in Python / R.
  • Experience building end-to-end analytics solutions, including exposing Python and R algorithms as APIs to be consumed in other services.
  • Maintain and improve existing machine learning applications. Quantify and analyse model performance and oversee model scaling and refreshing.
  • Knowledge of machine learning methods for classification and regression.
  • Some conceptual understanding of the underlying mathematics of the data science methods you use.
  • Experience with SQL and NoSQL databases.
  • Knowledge of visualisation libraries and tools (e.g. Plotly, D3.js, PowerBI).
  • Experience with or knowledge of some the following technologies: Docker, GitHub, Microsoft Azure/AWS/Google Cloud, Microservices and Spark