Data Analyst - Data Analityk in London

Data Analyst - Data Analityk in London

London Full-Time 30000 - 40000 £ / year (est.) Home office (partial)
Made Tech

At a Glance

  • Tasks: Analyse data, create reports, and provide insights to help public sector organisations thrive.
  • Company: Join Made Tech, a forward-thinking company transforming public services with data.
  • Benefits: Enjoy 30 days holiday, flexible working, and a range of health and wellness perks.
  • Other info: Be part of a diverse team committed to inclusivity and continuous improvement.
  • Why this job: Make a real difference by helping organisations become data-led and improve lives.
  • Qualifications: Experience in data analysis, visualisation tools, and mentoring junior analysts.

The predicted salary is between 30000 - 40000 £ per year.

hackajob is collaborating with Made Tech to connect them with exceptional professionals for this role.

As a Senior Data Analyst at Made Tech, you’ll play a pivotal role in helping public sector organisations become truly data-led. You’ll join our data team in its mission to get data knowledge and skills out of silos and embedded into delivery teams. You will provide advanced data modelling, predictive analytics, and data visualisation, allowing us to deliver more sophisticated and customised solutions to our clients.

The role is very hands-on and you'll support as a senior contributor role 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.
  • Mentoring junior analysts, leading data-focused projects, and setting best practices in data analysis.
  • Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis.
  • Synthesis of research data: Experience in synthesising research data to present actionable insights and solutions.
  • Capability to advise on the choice and application of analytical techniques and critique colleagues' findings to ensure high standards in data analysis.
  • Understanding of data sources and storage: Knowledge of various data sources, data organisation, and storage practices.
  • Advocacy for data governance: Experience in advocating for data governance standards and influencing team adherence to data quality practices.
  • Ability to communicate and implement continuous improvements in data management practices through documentation, training, and regular team engagement.
  • Proficiency in defining and supporting common toolsets for data management, ensuring efficiency and seamless integration.
  • Automation of data management: Experience in automating data management activities to streamline processes and increase accuracy.
  • Compliance with data governance policies: Understanding and ensuring compliance with data governance policies, maintaining data security and ethical standards.
  • Data modelling expertise: Proficient in conceptual, logical, and physical data modelling.
  • Data cleansing and standardisation: Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques.
  • Use of data integration tools: Skilled in using ETL tools for data integration and storage.
  • Collaboration with data professionals: Experience collaborating with other data professionals to improve modelling and integration standards and patterns.
  • Ability to interpret data visualisation requirements and create meaningful, visually appealing representations tailored to the audience.
  • Experience with tools such as Tableau, Power BI, and Python libraries like Matplotlib and Seaborn.
  • Data quality assurance: Experience in implementing processes for data quality assessment and improvement, including data profiling, cleansing, and standardisation.
  • Data validation and linkage: Ability to perform data validation checks and integrate data from various sources to ensure consistency and accuracy.
  • Data cleansing and preparation: Proficiency in defining data cleansing processes and preparing data for analysis by handling missing values, outliers, and duplicates.
  • Communication of data limitations: Skilled in articulating data constraints and limitations to stakeholders, providing context for informed decision-making.
  • Peer review and quality control: Experience in conducting peer reviews to validate data outputs, ensuring high standards of accuracy and reliability.
  • Proficient in various statistical methods, such as hypothesis testing, regression analysis, clustering, and time series analysis.
  • Data analysis and interpretation: Experience in using statistical software or programming languages to perform data analysis and generate insights.
  • Skilled in presenting complex data in a clear, understandable manner tailored to diverse audiences, including senior management.
  • Ability to apply logical and creative thinking to resolve complex problems by breaking them down and generating innovative solutions.

We’re committed to building a happy, inclusive and diverse workforce.

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.

  • 30 days Holiday - we offer 30 days of paid annual leave.
  • Flexible Parental Leave - we offer flexible parental leave options.
  • Remote Working - we offer part-time remote working for all our staff.
  • We offer paid counselling as well as financial and legal advice.

An increasing number of our customers are specifying a minimum of SC (security check) clearance in order to work on their projects. Eligibility for SC requires 5 years' UK residency and 5 years' employment history (or back to full-time education).

We help organisations transform, deliver and manage world-class digital products and services. We’re helping local authorities make it easier and quicker for people to log housing repairs online. By digitalising access to NHS services we’re making it more accessible, such as children needing mental health support. We’re helping to drive better environmental outcomes by improving network performance through real-time asset monitoring, which means less wasted energy.

We were recently named as a finalist in the Raising the Bar for Workplace Transparency Award in the Shift People Awards.

Made Tech

Contact Details:

Made Tech Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Analyst - Data Analityk in London

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 - Data Analityk 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 - Data Analityk 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 - Data Analityk in London

Data Analysis
Predictive Analytics
Data Visualisation
Power BI
Tableau
Quicksight
Statistical Analysis

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.