Insight Analyst

  • WorldRemit
  • London, UK
  • Apr 05, 2019
Full time Business Development Data

Job Description

The Company

WorldRemit is changing the way people send money abroad. We’ve taken something complicated and made it simple. Tap the WorldRemit App or click our website and your international transfer is made – to a bank account, cash pickup, Mobile Money, or airtime top-up.

Changing the world isn’t easy – so we only hire the most talented people. You need to think differently, believe in new solutions to old problems, and have the drive to make them happen.


The Role and Opportunity

WorldRemit is sending remittances from over 50 send countries to over 140 receive countries and the number is growing monthly. Each of these corridors have different commercial and competitive characteristics

We are looking for an Insight Analyst that will support our data driven culture, leveraging the ever-expanding range of data sources we have available to make better decisions, from exploring our competitive landscape to understanding the way customers use our service.

Our team supports the business across all different areas, so we tackle a wide variety of problems, ranging from the highest macro level (e.g. identifying patterns across countries) to the most specific operational issues (e.g. automatic identification of the drivers of payment failures), and most importantly we support the business at strategic level (e.g. creating customer models to build more value).

This is an amazing opportunity for a data driven individual to play a key role in the continued growth of one of the UK’s leading FinTech companies; and a very exciting challenge to put analytical skills to the test against an international context.



On the business side, work closely with a variety of stakeholders across the company, understanding the key areas where we can make a difference. You will create analytical solutions, extract insights and propose actions based on solid data analysis and modelling.

On the technical side, you will be working with a wide variety of technologies (e.g. the Amazon Big Data ecosystem, Tableau, Python…) to retrieve and analyse the data, and applying your mathematical and statistical skill to obtain insights.

More specifically, to:

  • Translate business questions from different departments (e.g. finance, marketing, fraud, operations, customer service etc.) into specific hypotheses that can be answered quantitatively with our data
  • Contribute to the industrialization of analytics, creating reproducible analysis that can provide insight in a continuously moving environment
  • Support the creation of models that will help us understand the market behaviour
  • Devise methodologies that will allow us to evaluate the impact of projects on the different business KPIs
  • Identify opportunities for improvements through data analysis, and champion the usage of data to derive commercial insights and drive action across the business
  • Present results to key stakeholders

Key Attributes

  • Excellent analytical problem-solving skills in a very dynamic environment, able to tackle problems from multiple areas of the business.
  • Capable of developing full analytical projects end to end, from the business problem to the final insights and actions.
  • Passion for learning, able to quickly adopt new business concepts and technologies.

Skill and Experience

  • 2+ years of experience in data analysis within a business to consumer industry, preferably in financial services or technology. Experience in international markets and/or fast-growing companies particularly valued.
  • Very strong SQL skills, able to handle complex data structures from multiple sources (Big Data, conventional DBs) and different areas (digital, transactional, marketing…)
  • Experience building dashboard or self-serve tools, with preference for Tableau.
  • Strong analytical capability and evidence of being able to transform data into actionable insights.
  • Experience using mathematical/statistical methods to create models and/or forecasts. Familiarity with statistical software is a plus, particularly R or Python.