INSPIRE SUCCESSFUL DECISIONS
Kantar’s Worldpanel division is searching for a curious, dynamic and creative graduate to join us as a Junior Data Analyst. Based in Lisbon, Portugal this is truly an incredible opportunity to be part of our exciting vision for the future!
The Team and Role’s mission
Are you passionate about decoding shopper behaviour and using data to answer tough questions? Do you thrive in a dynamic environment where your analytical skills can directly impact business strategies?
By joining our Global Analytical Development Teams as a Junior Data Analyst at Kantar Worldpanel, you'll work with the richest consumer panel dataset in the world, helping global clients understand and predict shopper behaviour across various markets, including FMCG, Tech, Beauty, and Fashion. We expect you to develop expert level data wrangling skills in R, SQL and Python which you’ll be expected to apply to our disaggregated datasets to create analytic solutions as well as having to actively developing Power BI Dashboards to help us tailoring compelling stories to our clients.
You’ll also be able to evolve in a variety of ways – as some of our Data Analyst have gone on to become Data Scientists, Data Engineers or even Project Managers that take on and lead challenging projects. With us, you’ll have the opportunity to develop your skills depending on business requirements and your interests, you’ll be able to progress onto learning and working with Angular, Databricks, Spark, Docker or Kubernetes. You could end up building front-end applications which help tell stories that our global clients will use to build their business strategies; or even using modelling techniques such as regression, decision trees and clustering.
If you're ready to make a meaningful impact on a global scale, apply for a career that’ll be out of the ordinary and join us!
Key outcomes
- Support various data-related projects across different departments, by working with diverse data sets to clean, manipulate, and analyse data using tools such as R and Python.
- Conduct thorough data quality checks and ensure the integrity of the data.
- Apply a range of statistical techniques and modelling processes to transactional and attitudinal data.
- Understand industry best practices for data modelling to organise the data behind Power BI reports.
- Develop and maintain interactive Power BI dashboards in order to translate complex data sets into easy-to-understand visualizations for stakeholders.
Key Capabilities
Your background will ideally look like this…
- University Degree (Bachelor’s or Master’s Degree) in Statistics, Mathematics, Data Science, or equivalent fields.
- Business proficiency in English (B2 Level Minimum Required).
- Demonstrable experience with data analysis, either through academic coursework, projects, or internships.
- Comfortable programming skills in R and/or Python will be required.
- Experience or knowledge in SQL for database management and querying.
- Familiarity with Power BI or other relevant data visualization tools.
With the following qualities…
- A passionate learner willing to set aside hours each week to upskill yourself and progress quickly with the tools at your disposal.
- Inquisitive, with critical thinking, and demonstrates a genuine passion for consumer behaviour.
- Enjoys actively looking for new and more efficient ways of improving processes, raising standards, reducing errors, and overcoming omissions.
- Is proactive, optimistic, and willing to get involved to achieve the team's goals and objectives.
- Is highly collaborative and adaptable with the ability to work effectively within different cultural and technical environments.
- Possesses outstanding communication and interpersonal skills in order to comfortably connect with partners at all levels across the organization and facilitates discussions in a constructive manner.
What our Recruitment Process Looks Like...
- 1st Stage – Numerical Reasoning Assessment Test.
- 2nd Stage – Screening Interview with Talent Acquisition.
- 3rd Stage – Technical interview with Hiring Managers.