Data Analyst

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., 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

• Manage expectations and interact across technical and business stakeholder groups.
• Maintain active updates, respond to inquiries, and foster collaborative environments.
• Translate basic business requirements into technical solutions.
• Simplify complex data insights into clear presentations for various audiences.

Logical & Creative Thinking

• Break down problems logically and generate structured solutions.
• Make informed decisions, prioritize tasks, and resolve issues efficiently.
• Demonstrate adaptability, curiosity, and a strong continuous learning orientation., Our hiring process is designed to be thorough, transparent, and supportive, guiding candidates through each step. The exact process may vary slightly depending on the role but these are the typical steps candidates can expect.

We’ll keep you updated throughout the process and provide helpful feedback at each stage. No matter the outcome, we make sure the feedback is useful and supportive, so you feel informed and can learn from the experience.

Our talent team will review all applications, and while we may use AI to help speed up the process, a real human will always make the final decisions. Once reviewed, shortlisted applicants will be invited to a screening.

This is a 25-30 minute call with someone in our talent team who is hiring for the role.

Once screenings have taken place the hiring manager will review the shortlist and invites to interview will be sent.

You may then be invited to an initial virtual interview which is usually with the hiring manager or a couple of members from the team. This is usually around 45 - 60 minutes and the format may vary depending on the role.

If you progress, you’ll be invited to a final stage interview which is usually with two members of the team. The format varies depending on the role and this is usually an hour.

• Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis.
• Experience in synthesising research data to present actionable insights and solutions.
• Ability to articulate the impact of their analysis on decision-making and problem-solving.
• Effective communication skills to engage and gain buy-in from sceptical colleagues.
• Familiarity with common data sources and general knowledge of data organisation and storage practices.
• Understanding of data governance standards and a commitment to following data quality practices set by the team.
• Ability to contribute to improvements in data management practices by supporting documentation, learning from team training, and actively participating in discussions
• Experience with using data management tools, with a willingness to learn more about maintaining efficiency and integration.
• Basic understanding of data governance policies, with a focus on following data security and ethical standards.
• An interest in learning how to automate data management activities to streamline processes and improve accuracy (desirable).
• Experience with conceptual, logical, and physical data modelling. Ability to adhere to data modelling standards and best practices.
• Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques.
• Basic experience with ETL tools for data integration and storage, with a focus on learning how to ensure data interoperability with other datasets.
• Some experience working with other data professionals, with a focus on learning and improving data modelling and integration practices through teamwork., An increasing number of our customers are specifying a minimum of SC (security check) clearance in order to work on their projects. As a result, we’re looking for all successful candidates for this role to have eligibility. Eligibility for SC requires 5 years’ UK residency and 5 year’ employment history (or back to full-time education). Please note that if at any point during the interview process it is apparent that you may not be eligible for SC, we won’t be able to progress your application and we will contact you to let you know why.

We’re committed to building a happy, inclusive and diverse workforce. You can get a sense of what it’s like working here from our blog, where we talk about mental health, communities of practice and neurodiversity as well as our client work and best practice. Like many organisations, we use Slack to chat to each other. The Slack groups that have formed give an idea of the diversity within Made Tech. If you’d like to speak to someone from one of these groups about their experience as an employee, please let one of the Made Tech Talent Team know. The groups are:

• antiracist-activists
• disability
• lgbtqiaplus-allies-and-activists
• neurodiversity
• parents-carers
• Womxn-in-tech

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