Preparing for an interview at The Information Lab requires a blend of technical curiosity, design awareness, and strong communication skills. You do not need to be an expert in Tableau or Alteryx from day one, but you must demonstrate an exceptional willingness to learn and adapt.

Coachability & Feedback Integration – This is perhaps the single most critical evaluation criterion. Throughout the process, interviewers will give you direct, sometimes blunt feedback on your dashboards. They are evaluating whether you take this feedback personally or use it as fuel to improve. Demonstrate your strength here by actively listening, asking clarifying questions, and quickly implementing their suggestions in your next iteration.

Analytical Storytelling – A great dashboard is more than a collection of pretty charts; it must tell a cohesive story. You must structure your visualizations using the 5 W's framework: What, Where, Who, Why, and When. Interviewers look for your ability to extract meaningful business insights from raw numbers and present them in a logical, narrative-driven flow.

Communication & Presentation Skills – As a Consultant, you will represent The Information Lab in front of major clients. You must be able to present your work clearly, confidently, and concisely. Practice delivering your presentations within strict time limits (often exactly five minutes) and prepare to defend your design and analytical choices under questioning.

Drive & Self-Guided Learning – Because the program is designed to train you from the ground up, interviewers look for a proven track record of self-education. Show that you have spent hours researching visualization principles, watching training videos, and practicing your skills independently.

The interview process at The Information Lab is uniquely structured to simulate the real-world lifecycle of a data consulting project. It is highly interactive, supportive, and designed to evaluate your growth potential rather than just your current resume. The entire process typically spans four to six weeks.

The journey begins with you choosing a dataset that genuinely interests you and building an initial dashboard using Tableau Public. Once submitted, you will receive constructive feedback from the team. This is a crucial test: you are expected to refine your dashboard based on this feedback and resubmit it. If your second version meets the benchmark, you will move to a preliminary interview. This round involves a video call where you present your dashboard and answer consulting scenario questions.

If you pass the preliminary round, you will enter the final stage. You and other finalists will be given a complex, standardized dataset. You will have a set amount of time to clean the data, build a professional dashboard, and prepare an in-person presentation at our offices (such as the London St Paul's office). During this final day, you will present to a panel, answer technical and process questions, critique an example dashboard to show your eye for design, and participate in a formal competency and culture-fit interview.

The visual timeline above outlines the progression from your initial open-ended visualization to the structured, high-pressure final stage. It shows how the process shifts from testing your raw drive and learning ability to evaluating your performance under consulting constraints. Candidates should use this timeline to pace their preparation, ensuring they dedicate sufficient time to the intensive dashboard-building phases.

To succeed in this process, you must understand the specific technical and consulting dimensions on which you will be evaluated.

Dashboard Design & Data Visualization Principles

This area focuses on your ability to translate raw data into clean, functional, and intuitive visual interfaces. You are evaluated on your layout choices, color theory, and chart selection.

Be ready to go over:

• Visual Hierarchy – How you position key metrics (KPIs) at the top and structure the dashboard to guide the user's eye naturally.
• Chart Selection – Choosing the right chart for the right data (e.g., line charts for trends over time, bar charts for comparisons, avoiding cluttered pie charts).
• Color Theory – Using color purposefully to highlight key insights rather than purely for decoration, and avoiding problematic or confusing color choices.

Advanced concepts (less common):

• Dashboard interactivity using parameters and actions.
• Designing for accessibility (e.g., color-blind friendly palettes).
• Performance optimization for large datasets.

Example scenarios:

• "Walk us through your dashboard and explain why you chose a scatter plot instead of a bar chart to show this relationship."
• "Critique this sample dashboard and point out three design choices that hinder its usability."

Coachability & Feedback Loop

This evaluation area measures your psychological safety, openness to criticism, and speed of learning. The interviewers want to see how you react when your hard work is critiqued.

Be ready to go over:

• Receiving Feedback – Maintaining professional composure and showing genuine interest when interviewers point out flaws in your dashboard.
• Iterative Improvement – Demonstrating a clear evolution between the first draft of your dashboard and your final submission.
• Active Listening Clarifying the 'why' behind the feedback rather than blindly implementing changes without understanding.

Example scenarios:

• "We noticed your color palette here is quite distracting. If we asked you to redesign this using only three colors, how would you restructure your visual cues?"
• "Explain how you incorporated the feedback we sent you after your first submission."

Consulting Delivery & Client Management

As a consultant, you must build trust with clients. This area evaluates your verbal communication, presence, and ability to handle difficult stakeholder dynamics.

Be ready to go over:

• The 5 W's Framework – Explaining the What, Where, Who, Why, and When of your data narrative during your presentation.
• Time Management – Delivering a comprehensive, high-impact presentation within a strict five-minute limit.
• Handling Ambiguity – How you approach a complex, messy dataset with minimal instructions.

Example scenarios:

• "Imagine a client tells you that they do not trust the data source you used. How do you handle that conversation?"
• "How would you explain the concept of a 'parameter' to a business stakeholder who has never used Tableau?"

On a day-to-day basis, a Consultant at The Information Lab balances client work, continuous technical training, and community engagement. You will act as a trusted advisor to clients, helping them unlock the value of their data assets.

You will spend a significant portion of your time working directly on client engagements. This involves gathering business requirements, connecting to various data sources, cleaning and structuring data using tools like Alteryx or Tableau Prep, and building interactive dashboards. You will not work in a silo; you will collaborate closely with client stakeholders, business analysts, and IT teams to ensure your solutions align with their business goals.

Another core responsibility is knowledge sharing and education. You will often train client teams on how to use the dashboards you have built and how to adopt self-service analytics. Additionally, you will contribute to the broader data analytics community by writing blog posts, participating in industry events, and helping train subsequent cohorts of the Data School.

While technical skills can be taught, certain foundational qualities and mindsets are essential to be competitive for the Consultant role.

• Must-have skills and attributes:

  • A highly analytical mind with a passion for problem-solving and finding patterns in data.
  • Strong verbal and written communication skills, with the ability to present complex ideas clearly.
  • High coachability and a demonstrated ability to accept, process, and implement constructive feedback.
  • Strong self-motivation and the grit to spend hours learning complex software independently.
  • Basic data literacy (understanding concepts like averages, percentages, and basic data relationships).

• Nice-to-have skills:

  • Prior exposure to Tableau Public, Alteryx, SQL, or other business intelligence tools.
  • Experience in a client-facing or customer service role.
  • A background in design, UX/UI, or visual arts, which can aid in creating beautiful dashboards.