Data Analyst

Data Analyst

Department: Technology

Employment Type: Permanent

Location: Any UK Office Hub (Bristol / London / Manchester / Swansea)

Compensation: £37,000 - £45,000 / year

Description

About Made Tech: Our aim at Made Tech is to use human-centred technology to improve our society. We believe putting people at the heart of designing, building and delivering public services leads to better outcomes 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.

As a Data Analyst, you may play one or more roles according to our clients' needs. The role is very hands‑on and you'll support as contributor for a project, focusing on:

• 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.

You’ll need to have a drive to deliver outcomes for users. You’ll make sure that the wider context of a delivery is considered and maintain alignment between the operational and analytical aspects of the engineering solution.

Key Responsibilities

Analysis & Synthesis

• Apply statistical, qualitative, and data mining techniques tailored to research contexts.
• Synthesize data to deliver actionable insights and articulate impacts on decision‑making.
• Engage effectively with skeptical colleagues to build consensus and buy‑in.

Data Management

• Maintain data accuracy, accessibility, and storage using common data sources.
• Adhere to team data governance, security, and ethical standards.
• Support continuous improvement, documentation, and process automation (desirable).
• Utilize and learn data management tools to maintain integration and efficiency.

Data Modeling, Cleansing & Enrichment

• Design conceptual, logical, and physical data models using best practices.
• Perform data cleansing and standardization to resolve quality issues.
• Gain exposure to ETL tools to ensure data interoperability across datasets.
• Collaborate with data professionals to refine modeling and integration practices.

Data Visualization

• Create visually appealing representations tailored to audience requirements.
• Apply visualization tools (e.g. Tableau, Power BI, Matplotlib, Seaborn).
• Follow core design and accessibility principles to produce clear, accurate visuals.
• Incorporate peer feedback to refine visualization quality.

Quality Assurance, Validation & Linkage

• Conduct data profiling, validation checks, and multi‑source data linkage.
• Prepare datasets by managing missing values, duplicates, and advanced cleansing.
• Communicate data limitations to assist stakeholders in informed decision‑making.
• Participate in peer reviews to uphold data accuracy standards.

Statistical Methods & Data Analysis

• Execute statistical techniques including hypothesis testing, regression analysis, and clustering.
• Analyze data via programming languages/software to share insights with technical and non‑technical audiences.
• Explore and apply emerging statistical methodologies to real‑world problems.

Business Skills