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Data scientist (planning data insights)

London
London Gov
Data scientist
€55,000 a year
Posted: 20 May
Offer description

Good Growth

Good Growth is responsible for delivering and implementing the Mayor’s environment, transport and economic strategies and for the effective implementation of the London Plan. The Directorate is also responsible for regeneration (where the programme is not housing led), enterprise, growth, capital projects and design work.


About the role

Making the best use of land to support housing, infrastructure and sustainable growth is one of the biggest challenges facing cities today.

As a Data Scientist in the GLA’s Planning & Regeneration Unit, you will take a leading role in generating data-driven insights on city planning in London, supporting key programmes across planning, housing, and infrastructure delivery.

You will help shape an emerging insights programme in Planning + Regeneration’s Data & Digital team, extracting and communicating actionable, policy-relevant insights from the Planning London DataHub, which brings together planning application and development proposal data from all London planning authorities.

You will be a super-user, advocate and steward for this dataset, understanding its structure and shaping requirements for downstream users across reporting, data inputting and modelling projects across London’s planning ecosystem.

We are looking for someone who can combine strong policy awareness with advanced data analytics expertise, is comfortable working collaboratively with both technical and non-technical specialists, and is eager to make data accessible, engaging, and useful.


What your day will look like

You will turn complex planning data into useful insight across three related areas of work:

* Data modelling: Contributing to the development of the Planning London DataHub and other planning data services, including defining target architecture for data pipelines from databases to front-end systems, working closely with the PLD Delivery Manager
* Statistical analysis & research: Collaborating with policy officers and data scientists to extract insights from planning and related datasets, helping to inform policy decisions, the London Plan evidence base and wider planning policy work. This could include scenario modelling, risk analysis and trend forecasting across London’s development pipeline
* Reporting and insights: Leading production of the London Plan Annual Monitoring Report and associated data publications and insights briefings, summarising key indicators on the planning system, providing narrative interpretation, and acting as a key source of quantitative insight on how the system delivers against strategic priorities

Across this work, you will help build the wider planning data ecosystem, working with policy teams, boroughs, SMEs and technical specialists to turn user needs into robust analytical projects, reusable tools, open data outputs and clearer evidence for decision-making across London.

You will be embedded with a team of data project specialists, work closely with planning policy and delivery experts, and connect to a wider network of friendly and ambitious data scientists, engineers, and GIS specialists using data to support London’s sustainable growth across the GLA.


Skills, knowledge and experience

To be considered for the role you must meet the following essential criteria:

* Problem formulation: Ability to frame complex policy questions and translate them into practical analytical approaches using high-volume, multi-source datasets
* Communicating insights: Ability to communicate data and insights clearly with non-technical stakeholders in written, verbal and visual formats
* Statistical analysis: Strong grasp of statistical techniques, including regression and cluster analysis, and experience applying them to real-world problems
* Built environment experience: Experience working with data in spatial planning, infrastructure, housing or a related built environment field, ideally in London
* Statistical programming: Strong Python skills, with experience implementing statistical techniques and machine learning methods in code and building reproducible analytical processes
* Quantitative training: A postgraduate degree in a quantitative field strongly related to data science, involving applied mathematics, statistics and coding, or equivalent professional experience

The GLA Competency Framework Guidelines further detailing each competency and the different level indicators can be found here: GLA Competency Framework


Equality, diversity and inclusion

London's diversity is its biggest asset, and we strive to ensure our workforce reflects London's diversity at all levels. We welcome applications from everyone regardless of age, gender, gender identity, gender expression, ethnicity, sexual orientation, faith or disability.

We particularly encourage applications from Black, Asian and Minority ethnic candidates and disabled candidates who are currently underrepresented in our workforce.

We are committed to being an inclusive employer and we are happy to consider flexible working arrangements. We would welcome applications from candidates who are seeking part time work as this role is open to job share.

Please note we are a Disability Confident Employer so for candidates who wish to be considered under the scheme and meet the essential criteria, they will automatically be invited to interview. Please note, should you require any adjustments through the process, we will accommodate as much as possible. Please contact the recruitment team for further information if required.

GLA staff are hybrid working up to 3 days a week in our offices and remotely depending on their role. As part of this, you will need to split your time between home working and coming into the office.


Benefits

In addition to a good salary package, you will be paid every four weeks, providing frequent salary payments. We also offer an attractive range of benefits including 30 days’ annual leave, interest free season ticket loan, interest free bicycle loan and a career average pension scheme.

Note: successful candidates must undergo a criminal record (DBS) check but some roles may require additional security screening.

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