Data Scientist in Glasgow

Job Title: Data Scientist (HEO)

Grade: HEO • Total remuneration: £50,872 – £58,240 • Pay Supplement: Digital, Data and Technology Annual Pay supplement 24% included • Pension: 28.97% (RoS contribution) • Annual leave: 38 days (42 days with length of service) • Duration: Permanent • Working Pattern: 35 hours per week (flexible) • Location: Hybrid – Meadowbank House, Edinburgh (EH8 7AU) or St Vincent Plaza, Glasgow (G2 5LD)

Role Overview

This new generalist role aims to grow our data science capability and promote the use of data‑driven methods, including ML/AI, across the organisation. You will collaborate with multiple teams to tackle complex business problems, extract value from unstructured and semi‑structured land and property data, support decision‑making and deliver new data products for internal and external customers.

Key Responsibilities

• Work closely with colleagues to identify, formulate and solve business problems using data.
• Explore, analyse and transform complex land and property data from a range of formats.
• Develop rule‑ or model‑based methodologies to discover knowledge, extract structure from semi‑ or unstructured data, automate training data creation, train and adapt ML/AI models, create internal/external data products, data‑driven tools and reports, and monitor data quality.
• Design experiments, determine suitable evaluation strategies and metrics, and evaluate outputs.
• Document methodologies to deliver reproducible and explainable work.
• Gather feedback and monitor the continued performance and accuracy of outputs.
• Participate in team development activities, strategic discussions and communities of practice.
• Contribute to the delivery of data science projects using Agile data science methodologies.
• Build understanding of Registers of Scotland data, business processes, strategic objectives and the policy environment.
• Communicate insights and results to technical and non‑technical audiences using visualisation and data storytelling.
• Build awareness of technical and regulatory standards and developments in industry.

Essential Criteria – Skills and Attributes for Success

Technical Experience

• Qualified in a quantitative field such as Data Science, Computer Science, or equivalent experience.
• Proficient at problem‑solving using a broad range of data analysis and data science tools and approaches.
• Experience working with structured, semi‑structured and unstructured data types; knowledge of graph and/or spatial data formats is an advantage.
• Working knowledge of common machine learning model architectures and training processes.
• Experience using foundational models (LLMs) to create simple solutions.
• Competent in coding for data science using common Python libraries such as spaCy, regex, scikit‑learn, PyTorch, NumPy, pandas, etc.
• Competent at SQL querying and interacting with databases using Python.
• Working understanding of ML Ops workflows.
• Some practical experience with the AWS stack, including SageMaker.
• Demonstrates good coding practice.
• Comfortable working in a Linux environment.

Essential Experience

• Demonstrable business awareness and understanding of how data science can drive value and support strategic objectives.
• Familiarity with product delivery life cycles and workflow management tools.
• Ability to convey complex topics in a clear and concise manner.
• Understanding of Data and AI Governance considerations – ethics, transparency, explainability, licensing and regulation.
• Experience working in a highly regulated sector is an advantage.

Behaviours

At the application stage, you will be scored against the following behaviours.

• Changing and Improving
  • Seek out and respond to feedback.
  • Work with others to improve and implement change to team ways of working.
  • Connect own work to business goals through improved understanding of processes and data.
  • Continuously develop skills through role‑specific learning.
• Communicating and Influencing
  • Show positivity and enthusiasm towards solving complex data challenges.
  • Clearly present and explain own work to stakeholders.
  • Understand the business and its customers and how Data Science can deliver value to them.
  • Confident in providing evidence to influence and support decisions, checking audience understanding.
• Working Together
  • Work closely with stakeholders such as fellow data scientists, analysts, business analysts, product managers, subject matter experts, developers, ML/AI engineers, Agile and developer coaches.
  • Collaborate with others to create and use shared technical resources, tools and support.
  • Contribute to knowledge sharing sessions, communities of practice and peer reviews.
  • Build positive relationships with colleagues across teams and disciplines.
• Managing a Quality Service and Delivering at Pace
  • Manage work effectively in an Agile environment, focusing on stakeholder needs and business priorities.
  • Manage uncertainty by tracking progress, being flexible and remaining transparent about challenges.
  • Apply good engineering and data science practice consistently across projects and activities.
  • Document all work to ensure continuity of service.

EEO Statement

Nationality and immigration status. In general, only nationals from the United Kingdom, the Republic of Ireland, and the Commonwealth are eligible for employment. EU nationals (with settled or pre‑settled status), certain EEA nationals, Swiss and Turkish nationals are also eligible. Detailed provisions on determining eligibility can be reviewed here.

Diversity and inclusion. We welcome applications from disabled candidates and from under‑represented groups, including people who are disabled, minority ethnic groups and young people (16‑24 years). We are committed to increasing diversity and welcome your contribution to our EDI strategy.

Salary & Benefits

• Pay range: £41,026 – £46,968 base salary, with Digital, Data and Technology Annual Pay supplement 24% included in total remuneration. • Pension: 28.97% (RoS contribution). • Annual leave: 38 days, increasing to 42 days with length of service.