Senior Data Scientist at Planning Inspectorate
Bristol BS1, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

26 Nov, 25

Salary

49462.0

Posted On

26 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

R, Norway, Hypothesis Testing, Python, Data Science

Industry

Civil Engineering

Description

JOB SUMMARY

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 to gain a better understanding about how the Inspectorate performs and will build AI/Machine Learning tools that will improve processes and promote data driven decisions.
The Senior Data Scientist will be working in a multidisciplinary team to see how outputs can be delivered more efficiently and that they keep pace with new technology and are future proof.
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

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

TECHNICAL SKILLS

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

  • 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.

NATIONALITY REQUIREMENTS

This job is broadly open to the following groups:

  • UK nationals
  • nationals of the Republic of Ireland
  • nationals of Commonwealth countries who have the right to work in the UK
  • nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities with settled or pre-settled status under the European Union Settlement Scheme (EUSS)
  • nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities who have made a valid application for settled or pre-settled status under the European Union Settlement Scheme (EUSS)
  • individuals with limited leave to remain or indefinite leave to remain who were eligible to apply for EUSS on or before 31 December 2020
  • Turkish nationals, and certain family members of Turkish nationals, who have accrued the right to work in the Civil Service

Further information on nationality requirements

Responsibilities

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 product
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