Data Analyst in Newport, Wales

Data Analyst in Newport, Wales

Newport +1 Full-Time 29700 - 36300 £ / year (est.) Home office (partial)
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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 dedicated to improving public services through technology.
  • Benefits: Enjoy 30 days holiday, flexible working hours, remote options, and a range of wellness benefits.
  • Other info: Be part of an inclusive team that values diversity and continuous learning.
  • Why this job: Make a real difference by using data to drive impactful decisions in the public sector.
  • Qualifications: Experience in data analysis, strong communication skills, and a passion for problem-solving.

The predicted salary is between 29700 - 36300 £ per year.

hackajob is partnering directly with Made Tech to hire for this role.

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.

About the role

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: 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.

Skills, Knowledge & Expertise

  • 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.

At this point, we hope you're feeling excited about Made Tech and the job opportunity. Get in touch with our talent team if you'd like an informal chat about the role and your suitability before applying. We are hiring for this role directly, so will not respond to any CVs sent via external recruitment agencies.

SC Eligibility

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 years' 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.

Support in applying

If you need this job description in another format, or other support in applying, please email. We believe we can use tech to make public services better. We also believe this can happen best when our own team represents the society that actually uses the services we work on. We're collectively continuing to grow a culture that is happy, healthy, safe and inspiring for people of all backgrounds and experiences, so we encourage people from underrepresented groups to apply for roles with us. When you apply, we'll put you in touch with a member of our talent team who can help with any needs or adjustments we may need to make to help with your application. We've put together this blog as a resource to share more about reasonable adjustments and some examples of what this could include. We also welcome any feedback on how we can improve the experience for future candidates.

Life at Made Tech

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.

Job Benefits

We are always listening to our growing teams and evolving the benefits available to our people. As we scale, as do our benefits and we are scaling quickly. We've recently introduced a flexible benefit platform which includes a Smart Tech scheme, Cycle to work scheme, and an individual benefits allowance which you can invest in a Health care cash plan or Pension plan. We're also big on connection and have an optional social and wellbeing calendar of events for all employees to join should they choose to.

Here are some of our most popular benefits listed below:

  • 30 days Holiday - we offer 30 days of paid annual leave.
  • Flexible Working Hours - we are flexible with what hours you work.
  • Flexible Parental Leave - we offer flexible parental leave options.
  • Remote Working - we offer part time remote working for all our staff.
  • Paid counselling - we offer paid counselling as well as financial and legal advice.

Locations

NewportWales

Data Analyst in Newport, Wales employer: Hackajob Ltd

JPMorgan Chase is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a Lead Site Reliability Engineer, you will not only tackle complex challenges but also benefit from extensive professional development opportunities and a strong commitment to diversity and inclusion. Located in a global financial hub, you'll be part of a team that values your expertise and encourages a culture of continuous improvement and technical excellence.

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Contact Details:

Hackajob Ltd Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Analyst in Newport, Wales

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 Hackajob Ltd!

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 Hackajob Ltd.

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 Hackajob Ltd.

Apply Directly through Our Website

When you find a suitable opening like Data Analyst at Hackajob Ltd, 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 in Newport, Wales

Data Analysis
Reporting
Business Intelligence (BI) Visualisation
Power BI
Tableau
Quicksight
Client Interaction

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 Hackajob Ltd, 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 Hackajob Ltd. 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 Hackajob Ltd

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 Hackajob Ltd!

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.