Senior Data Scientist - Planning Inspectorate - SEO

This Senior Data Scientist role is key to the development and delivery of innovative projects for key stakeholders in the Planning Inspectorate. The post holder will proactively analyse data from numerous sources in order to gain a better understanding about how the Inspectorate performs and will build AI/Machine Learning tools that will automate processes and promote data driven decisions. 

The Senior Data Scientist will also work closely with the rest of the team to see how outputs can be delivered more efficiently and that they keep pace with new technology and are future proof.

Job description

We are looking for a proactive, analytical thinker who is curious about data and keen to explore what insight it can add to the organisation.     

You will be highly motivated to help improve performance, working as part of a team with significant responsibility.      

You will need to be a good communicator, to help explain findings to stakeholders; and to explore areas for new or improved reporting and analysis.  

A typical day/week in this role will consist of:   

• Contributing to the data science community of practice within the Inspectorate  
• Working with stakeholders to identify areas of the organisation where data science can be applied to improve efficiency via automation and reproducible analytical pipelines  
• Using machine learning to create models that generate useful insight and communicating this to stakeholders to promote and support data driven decisions  
• Spending time learning and developing current or new skills  
• Maintaining and improving existing or new data science products

The Planning Inspectorate has a long and proud history in ensuring a fair planning system for England. The work we do has a significant impact on people’s lives, the communities where they live and the economy.

We want our colleagues to be able to work more flexibly and more collaboratively, exploring new and innovative ways to improve the way we provide services.

For further information on the Planning Inspectorate, please visit our careers page at Civil Service Careers

Office Attendance

This role is contractually based at Temple Quay House, Bristol which is currently out of use due to undergoing refurbishment work. In the interim, we have the use of alternative office space in very close proximity to Bristol Temple Meads railway station. We recognise and value the mutual benefits of hybrid working and have a flexible approach to in person attendance, which can vary dependent on the requirements of individual business units - the details of which can be discussed with candidates if invited to attend an interview.

Person specification

We will assess your application against the Essential Criteria and Success Profile elements listed:

Essential Criteria

• You will require a first or second class degree (i.e. a first, a 2:1 or a 2:2) in a relevant field (e.g. Data Science/Computer Science/Statistics).
• Experience of applied complex data analytics, machine learning and pattern recognition (e.g. machine learning techniques and algorithms for classification and regression, such as k-NN, Naïve Bayes, SVM, Decision Trees, etc).
• Strong experience with R or Python (including core data science libraries such as tidyverse, numpy, pandas, scikit-learn) to clean, manipulate, visualise, and model data.
• Experience communicating technical subjects and results to a non-technical audience to support data driven decisions.
• Good applied statistical skills, such as distributions, hypothesis testing, and regression.
• Good knowledge of ethical and privacy considerations when conducting analysis.

Desirable Criteria

• Knowledge of the UK Planning System
• Experience with Git

Qualifications

• You will require a first or second class degree (i.e. a first, a 2:1 or a 2:2) in a relevant field (e.g. Data Science/Computer Science/Statistics).

Behaviours

We'll assess you against these behaviours during the selection process:

• Changing and Improving
• Delivering at Pace
• Managing a Quality Service

Technical skills

We'll assess you against these technical skills during the selection process:

• • Good applied statistical skills, such as distributions, hypothesis testing, and regression.
• Good knowledge of ethical and privacy considerations when conducting analysis.