ROIVENUE is on a mission to help performance marketers around the globe simplify their workflow, achieve better ROI and save millions. Currently we are helping companies in six countries on two continents optimize budgets across dozens of markets. And we want more.
After a fair share of start-up adventures, ROIVENUE is now going through a major reboot phase and getting ready for scaling up. We are expecting more and more data and BI projects to take place.
That's where you come in.
ROIVENUE brings together data from multiple sources for marketers and serves them in both a ready-to-consume interface and raw data upon requests forms.
Not all clients have a data scientist or BI analyst in-house, though, and that's why they turn to us with questions and projects ranging from “We need to build easy dashboard for our C-level to consume” to “We need to calculate our acquisition and retention cost vs customer lifetime value” to “Our data look a bit odd, can you look at them and interpret, pls?”.
Your place will be with our Client Success department and your mission will be to figure out a way to satisfy these requests and then deliver these data projects to our client's satisfaction.
At the same time you will be a part of our internal data quality police team that makes sure ROIVENUE data can be 100% relied upon.
You want to work in a collective of young people with “anything is possible” mindset and you are preferably one of them.
You can see each new challenge as an opportunity to learn and you prefer change over status quo.
You always look for a better solution and never settle with the average.
You believe that data is beautiful and you are ready to show that to others.
Strong computer skills
Intermediate skill with common BI platforms in this order of preference: Microsoft Power BI, Google Data Studio, Tableau
Self-driven problem solver
Empathetic soul so that you can communicate effectively with different departments about their needs
Proficient oral and written English
Previous working experience within digital marketing and analytics industry and data sets
Proficiency with Google Analytics and its analytical and data concepts
Good knowledge of DAX and M language
Basic knowledge of SQL and/or Python
Basic experience with reading and finding information in API documentations