Higher Data Scientist - ( Ref : 6301 )

Natural England; Folly Gate; On-site; GBP 30,000 - 36,000; Full time

Job summary

A national environmental agency in England is seeking a Data Science professional to lead projects that enhance nature recovery. Candidates should have strong skills in R and/or Python, data analysis, and statistics. The role offers a salary of £30,850 with additional pension contributions and flexible working options.

Benefits

Civil Service Defined Benefit Pension scheme

Tailored learning and development

Flexible working environment

Culture of inclusion and diversity

Qualifications

• Good working knowledge of R and/or Python computer programming language for data science.
• Experience of data analysis, statistics and modelling techniques including exploratory data analysis.
• Competent in Git and GitHub for version control.

Responsibilities

• Lead the end-to-end delivery of analytical, modelling and data science improvement projects.
• Coordinate project planning and reporting to ensure efficiency.
• Engage with customers and partners to scope work and communicate progress.
• Build capability in others within the team.

Skills

R programming

Python programming

Data analysis

Statistical theory

Data visualisation

Git

GitHub

Job description

Data Science Services (DSS) is part of the Analysis Directorate. We are a large, national team and have broad skills including data science, analysis and statistics. We are passionate about quality technical delivery and continuous improvement, using novel data science approaches to help everyone understand nature recovery.

Responsibilities

• Lead the end-to-end delivery of analytical, modelling and data science improvement projects.
• Coordinate/undertake project planning and reporting so that projects are delivered efficiently, and progress, risks and issues are monitored.
• Ensure project data standards, processes and systems are followed to ensure outputs are high-quality and robust (including through good documentation and automation) so that customer decisions and advice can be based on sound evidence and outputs can be reproduced.
• Engage with customers and partners to scope work and communicate progress.
• Build capability in others in the team (and sometimes across NE as appropriate) to enable effective delivery and support resilience to absence and change.
• Engage with customers and partners to identify and exploit opportunities for new or revised projects (inc. use of new technologies), or for developing projects to improve the evidence base, improve efficiency, build capability or generate funding.

How to Apply

We welcome and encourage applications from all communities. Natural England is accredited to the Disability Confident Scheme, which denotes organisations which have a positive attitude towards disabled people. Disabled applicants who meet the minimum requirements for the role at the shortlisting stage are guaranteed an invitation to interview. If you require a reasonable adjustment at interview, or there is anything else you would like the panel to take into consideration, you should notify us of this at application stage where possible, or well in advance of your interview. This vacancy uses competency-based assessment. We'll assess you against the competencies below during the selection process: Technical Skills and Knowledge, Personal effectiveness, Creating resilient landscapes and seas, Work delivery. 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 doing so. Please note that STAR format is not required when answering the Technical Skills & Knowledge competency. Examples should be given in no more than 250 words for each competency. Competencies: Professional competency – Technical Skills and Knowledge, Professional competency – Creating resilient landscapes and seas, Professional competency – Work delivery, Personal effectiveness – Successful candidates must undergo a criminal record check. People working with government assets must complete baseline personnel security standard checks.

Competencies

• Technical Skills and Knowledge – Apply new technology to improve the way we deliver our work (Practitioner)
• Creating resilient landscapes and seas – Recognise environmental features and designations within their environmental context (Basic); Use and contribute to the evidence base on environmental and landscape change to support resilient landscapes and seascapes (Practitioner)
• Work delivery – Manage and deliver your work to meet agreed targets and deadlines (Practitioner); Handle data responsibly, understand your role in good governance, and comply with delegations, policies and procedures (Practitioner); Understanding of good practice, ethics, and quality assurance (verification, validation, analytical review) for data analysis
• Personal effectiveness – Successful candidates must undergo a criminal record check. People working with government assets must complete baseline personnel security standard checks.

Qualifications

• Good working knowledge of R and/or Python computer programming language for data science.
• Experience of data analysis, statistics and modelling techniques which could include exploratory data analysis, statistical theory, data visualisation and data science techniques.
• Competent in Git and GitHub for version control, collaborative development, and maintaining reproducible and well-documented code.

Benefits

• Alongside your salary of £30,850, Natural England contributes £8,937 towards you being a member of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides.
• Learning and development tailored to your role.
• An environment with flexible working options.
• A culture encouraging inclusion and diversity.
• A Civil Service pension with an employer contribution of 28.97%