At a Glance
- Tasks: Dive into data analysis, create insightful reports, and collaborate with clients to shape their data strategies.
- Company: Join Made Tech, a forward-thinking company focused on improving public services through technology.
- Benefits: Enjoy a competitive salary, flexible working locations, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real difference by using data to drive informed decisions in the public sector.
- Qualifications: Experience in data analysis and a passion for user-centric solutions are essential.
The predicted salary is between 37000 - 45000 £ per year.
Data Analyst
Department
Technology
Employment Type
Permanent
Location
Any UK Office Hub (Bristol / London / Manchester / Swansea)
Compensation
- 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
- #J-18808-Ljbffr
Data Analyst employer: Made Tech
Made Tech is an exceptional employer that fosters a collaborative and innovative work culture, where designers, researchers, and product professionals come together to make a meaningful impact in the public sector. With a strong emphasis on employee growth through mentorship and agile practices, team members are empowered to drive high-impact outcomes while enjoying the benefits of a supportive community dedicated to user-centred service delivery.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Made Tech!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analyst at Made Tech.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Made Tech.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst at Made Tech, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Made Tech, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Made Tech. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Made Tech
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Made Tech!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
