Data Analyst

Data Analyst

Full-Time 30000 - 40000 £ / year (est.) Home office (partial)
The Dot Collective

At a Glance

  • Tasks: Analyse complex datasets and create impactful data solutions.
  • Company: A forward-thinking consultancy focused on engineering excellence and empowering people.
  • Benefits: Flexible working, mental health support, and opportunities for personal projects.
  • Other info: Join a stable team that values collaboration and prioritises employee wellbeing.
  • Why this job: Make a real difference with data while enjoying a supportive and fun work environment.
  • Qualifications: Experience in data analysis, Python, and familiarity with cloud platforms.

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

We are a new generation consultancy based across the UK and EU, founded on the premises of engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects.

About you

Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you.

Your key skills and capabilities:

  • Gathering and documenting business and project requirements
  • Managing stakeholders of differing levels
  • Analysing and profiling large and complex datasets
  • Managing a team backlog using tools like Jira or Azure DevOps
  • Agile ways of working
  • Familiar with Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) systems
  • Creating conceptual, logical and physical data models
  • Creating mapping specifications for data migrations
  • Coordinating User Acceptance Testing (UAT) with business stakeholders
  • Knowledge of Python (pandas)
  • Experience with Cloud platforms
  • Creating data dashboards using Tableau, PowerBI or Qlik and storytelling

We expect you to work closely with the business to understand their current data problems, pain points, and to know how to analyse and cleanse their data. Also, we expect you to design data storage solutions and be a good communicator with your technical team.

Our promise to you

We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbaticals, and the ability to work on personal projects.

We believe that a gelled team is worth its weight in gold – we will do everything we can to avoid breaking well-performing teams – your team will be stable across different projects and you will work with people you trust and like.

We are committed to prioritising the wellbeing of our employees. To fulfil this promise, we provide a comprehensive employee wellbeing program that includes mental health support, flexible working arrangements, wellness activities, and a positive work culture.

We recognise that the world of tech delivery has moved on significantly in the last 15 years and know a thing or two about how to bring projects over the line without experiencing lots of despair and burn-out. In fact, we like to believe that our projects are the opposite of that – they are run smoothly and most of the time are fun to work on.

Data Analyst employer: The Dot Collective

As a forward-thinking consultancy, we prioritise the wellbeing and growth of our employees, offering a supportive work culture that values collaboration and innovation. With flexible working arrangements, comprehensive wellbeing programs, and opportunities to engage in meaningful projects, our Data Analysts can thrive in an environment that fosters both personal and professional development. Join us in a dynamic setting where your passion for data can truly make an impact.

The Dot Collective

Contact Details:

The Dot Collective Recruitment Team

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 The Dot Collective!

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 The Dot Collective.

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 The Dot Collective.

Apply Directly through Our Website

When you find a suitable opening like Data Analyst at The Dot Collective, 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 Analysis
Business Requirements Gathering
Stakeholder Management
Dataset Profiling
Agile Methodologies
Jira
Azure DevOps

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 The Dot Collective, 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 The Dot Collective. 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 The Dot Collective

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 The Dot Collective!

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.