Master thesis: Impact of customer pain points
Design and evaluate causal inference algorithm
What is causal inference?
The thesis
In this thesis projects the students will be mentored by our Head of Analytics, Viktor Granholm. In the fast-evolving world of micromobility, delivering a seamless customer experience is paramount. At Voi, we strive to understand the nuances of customer interactions with our e-scooter service to prioritise developments that truly resonate with users. This thesis project invites a student to use a causal inference model that quantifies the revenue impact of adverse customer experiences within the Voi ecosystem.
YOUR MISSION
You will work closely with our Analytics team to gain access to essential data and tools
A successful outcome of this thesis could be to:
- Design and refine a causal inference model to evaluate the revenue impact of negative customer events
- Create simulated event data or sensitivity analyses to test the model's effectiveness
- Package the model into a user-friendly format, empowering our R&D team to apply it to various customer pain points
STUDENT PROFILE
The students will be embedded in our Analytics team. We believe the right student have:
- A strong foundation in SQL, with proficiency in Python and statistical modelling being highly desirable
- A creative mindset, unafraid to explore new methodologies and approaches
- The ability to navigate open-ended questions autonomously and drive them toward concrete solutions