Data Analyst

Made Tech wants to positively impact the country's future by using technology to improve society, for everyone. We want to empower the public sector to deliver and continuously improve digital services that are user‑centric, data‑driven and freed from legacy technology. A key component of this is developing modern data systems and platforms that drive informed decision‑making for our clients. You will also work closely with clients to help shape their data strategy.

Key responsibilities

• Data analysis and reporting: Conducting in-depth data analysis, generating reports, and providing actionable insights for client projects.
• Data and BI visualisation: Producing BI dashboards using industry‑standard tools – Power BI, Tableau, Quicksight etc.
• Client interaction: Collaborating with clients to understand their needs, translating these into analytical solutions, and presenting findings in a clear, actionable manner.

Requirements

Analysis and synthesis

• Application of analytical techniques: Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis. Ability to select and apply appropriate techniques based on context.
• Synthesis of research data: Experience in synthesising research data to present actionable insights and solutions. Ability to articulate the impact of analysis on decision‑making.
• Engagement with sceptical colleagues: Effective communication skills to engage and gain buy‑in from sceptical colleagues.

Data Management

• Good understanding of data sources and storage: Familiarity with common data sources and general knowledge of data organisation and storage practices.
• Awareness of data governance: Understanding of data governance standards and commitment to following data quality practices.
• Continuous improvement: Ability to contribute to improvements in data management practices.
• Toolset support: Experience with data management tools and willingness to learn more.
• Interest in automation: An interest in learning how to automate data management activities.
• Compliance with data governance policies: Basic understanding of data governance policies and focus on data security and ethics.

Data modelling, cleansing, and enrichment

• Data cleansing and standardisation: Experience resolving data quality issues and ensuring data accuracy.
• Exposure to data integration tools: Basic experience with ETL tools for data integration.
• Collaboration with data professionals: Some experience working with other data professionals.
• Understanding visualisation requirements: Ability to understand visualisation needs and create simple, visually appealing representations.
• Good working knowledge of visualisation tools: Experience using tools like Tableau, Power BI, or Python libraries.
• Awareness of visualisation standards: Understanding of design principles for clear and accurate visualisations.
• Willingness to learn from peers: Open to feedback from senior team members to improve visualisations.

Data Quality Assurance, Validation, and Linkage

• Data quality assurance: Familiarity with data quality assessment techniques.
• Data validation and linkage: Experience performing basic data validation checks and combining data from different sources.
• Data cleansing and preparation: Experience in data preparation, including handling missing values and duplicates.
• Communication of data limitations: Ability to discuss data limitations with stakeholders.
• Participating in peer reviews: Willingness to participate in peer reviews to improve data accuracy.

Statistical Methods and Data Analysis

• Knowledge of statistical methods: Familiarity with common statistical techniques such as hypothesis testing, regression analysis and basic clustering.
• Data analysis and interpretation: Experience using statistical software or programming languages for data analysis.
• Willingness to learn new methodologies: Interest in exploring and applying new statistical techniques.

Communication

• Stakeholder communication: Some experience working with different types of stakeholders.
• Willingness to engage in active and reactive communication: Comfortable sharing updates and responding to inquiries.
• Interpretation of stakeholder needs: Ability to understand stakeholder requirements and translate into technical solutions.
• Presentation skills: Experience presenting data and insights to various audiences.

Logical and creative thinking

• Problem‑solving skills: Ability to apply logical thinking and generate solutions.
• Decision‑making and action‑taking: Experience in making informed decisions and prioritising tasks.
• Adaptability and learning orientation: Willingness to adapt to new challenges and continuous learning.

Benefits

• 30 days of paid annual leave plus bank holidays.
• Remote working for all staff.
• Paid counselling and financial and legal advice.

Security Clearance

All successful candidates must have eligibility for an SC clearance. SC eligibility requires five years of continuous UK residency. If at any point during the interview process it becomes apparent that you may not be eligible, the application will not proceed.

We encourage people from under‑represented groups to apply.