Senior Data Analyst - Natural Capital Ecosystem Assessment - ( Ref : 6688 )

Job summary

Job description

The team - The England Ecosystem Survey (EES) is Natural England’s largest ever field survey project – an ambitious and high-profile initiative to collect ecosystem data from a wide range of habitats across England. It is a cornerstone project within the Natural Capital and Ecosystem Assessment programme; led by Defra, and part of the government’s major projects portfolio.

The EES project is using professional survey as a tool to provide high quality data to assess the state and condition of biodiversity, ecosystems, and natural capital assets within England’s habitats and landscapes. It will address existing data gaps, including soils.

This person will be responsible for creating and maintaining some of the Reproducible Analytical Pipelines (RAPs) that underpin the management, processing and analysis of EES data.

As the project moves into a phase with greater focus on data publication and analysis, we are recruiting for someone to support in consolidating existing RAPs and creating new data science solutions for the management, processing, QA, and QC of EES data. They will work to further embed to use reproducible, accessible and efficient workflows to support the management of EES dataset products across the data lifecycle, from ingestion to publication.

They will work closely with the Principal Officer for Data and Analysis, Data Product Leads (responsible for individual data products) and analysts in the NCEA’s Data Engagement and Analysis Team.

The role will involve some travel at times throughout the year with potential overnight stays.

Job description

Key Tasks/Principal Accountabilities

• To create annotated and version-controlled R scripts for use in data ingestion, pre-processing, cleaning, quality assurance, quality control, analysis and visualisation
• Write and update functions to undertake processes related to data in R
• Produce reproducible analytical products and pipelines that are accessible to other users and promote their adoption across datasets to deliver standardisation and efficiency
• Work with the data lead (responsible for data product) and data owner (accountable for data product) to understand the requirements for data related tasks and create innovative reproducible analytical solutions
• Ensuring adherence to QFAIR, the Government Statistical Code of Practice and internal standards in managing, processing, analysing and publishing data
• Advocate for the adoption of standardised analytical solutions across EES datasets
• To create and / or maintain relational databases or geodatabases
• Supporting with formatting data for publication

Technical Skills and Knowledge

• Working knowledge of R, R Studio and GitHub (essential)
• Working knowledge of key packages and processes used for data processing, cleaning visualisation and analysis in R such (e.g. Dplyr, Tidyr and ggplot2) (essential)
• Working knowledge or R Markdown and R Shiny or the capability to learn these approaches (essential)
• The ability management and process data in accordance with internal standards and adherence to licensing restrictions (essential)
• Working knowledge of Python for data processing, cleaning, visualisation and analysis (statistical and geospatial) (desirable)
• Ability to prioritise work accounting for urgency and contingencies (essential)
• Working knowledge with the use of APIs (Application Programming Interface) to requests specific datasets from a server for use in the R Environment (desirable)
• The ability to work with ArcGIS or QGIS to process geospatial data (essential), the use of Python (desirable) and the use of R to undertake geospatial analysis (desirable).
• Working knowledge of SQL and Postgres (desirable)

When completing the application form you should present relevant examples using the STAR format. Give us an example of how you have demonstrated the competency (which can be work related or from another area of your life) and tell us about the Situation, the specific Task you had to undertake, the specific Actions you took, and the Result (both immediate and in a wider context) of your Action.

Please note that STAR format isnot required when answering the Technical Skills & Knowledge competency.

Examples should be given in no more than 250 words for each competency.

If you are successful at the shortlisting stage, you will be invited to attend an interview via MS Teams or a suitable alternative, where you will be asked to give examples for all competencies as set out in the Job Description.

As with all roles in NE, these roles require office attendance of a minimum of 20% of the working time – one day per week for those who work full time, subject to any reasonable adjustments and/or existing contractual homeworking

Please note: Artificial Intelligence can be a useful tool to support your application. However, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use.

If we receive a high volume of applications, Technical Skills and Knowledge will be used as an initial sift criterion, and the pass mark may be raised accordingly.

Competencies

Competence 1

Professional competency

Detail

Technical Skills & Knowledge

Description

• A broad knowledge of Natural England’s purpose, and the relevant frameworks and practical activities/approaches needed to deliver project results and achieve outcomes within own work area and when contributing to wider Natural England strategic objectives and work programmes.
  • You will be assessed against the Technical Skills and Knowledge criteria.

Competence 2

Professional competency

Detail

Leading and Managing People

Description

• Set clear plans and expectations for your team, explain reasons behind decisions, be clear on the outcomes to be achieved, and make things happen by sharing and delegating work to the right people (Practitioner)

Competence 3

Professional competency

Detail

Work Delivery

Description

• Manage and deliver your work to meet agreed targets and deadlines (expert)
  • Handle data responsibly, understand your role in good governance, and comply with delegations, policies and procedures (Expert)
  • Identify and apply the most appropriate data and methodologies for your analysis, utilising reproducible analytical pipelines and data science approaches where appropriate (Expert)

Competence 4

Professional competency

Detail

Personal Effectiveness

Description

• Make and explain objective decisions which combine your professional judgement and evidence (Expert)
  • P