Welcome to the third Helsinki Data Science Meetup of 2018! This time the meetup will take place hosted by VR on Thursday the 20thSeptember, 2018. Our location is at the VR Group Headquarters located on Radiokatu 3 (Iso Paja) in Pasila, Helsinki. Just 6 minutes walk from Pasila Railway Station.

The VR Group is a Finnish State owned enterprise that primarily operates in Finland, but also has operations abroad, including in Russia and Sweden. The VR group employs 7,500 professionals and prides itself on providing its customers with high-quality, environmentally-friendly passenger and logistics services. The VR Group has three main business operations revolving around customer groups. VR’s passenger services offer public transport services in commuter and long distance trains and buses. VR Transport offers road and railway logistics services, while VR Track is focused on infrastructure, maintenance and supplies railway materials. In September, we will hear about and learn from their success stories.


17:30 Snacks and Networking

18:00 Annika Nordbo, Head of Data Science, VR Passenger Traffic

Welcoming and Overview of the VR Data Science Architecture in AWS 

18:10 Heikki Pulkkinen, Data Scientist, VR Passenger Traffic

Finding Sales Anomalies with Casual Impact

End-to-end solution to detect local anomalies (music festivals, sport events etc.) Data from unrelated train connections was used as reference time series and the actual modeling was done with Google’s CausalImpact. Model is ran daily on AWS EC2, results are stored to Snowflake DWH and visualized with PowerBI.

Passenger Count Predictions

Using XGBoost to predict the number of passengers in each train at a given point in time. One of the most important parts of the architecture is measuring the training-serving skew from the multiple different models in production.

18:55 Break

19:10 Tuomas Karavirta, Data Scientist, VR Maintenance

From Laser Scanning of Wheels to Simulation of Rolling Dynamics: An Example of Condition Based Maintenance in Practise

VR has implemented a simulation algorithm that is currently being used to monitor wheelset dynamics. Maintenance decisions based on this data have led to significant improvements on wheelset lifetime and maintenance cost of SR2 locomotives.

19:50 Closing Remarks by Majella Clarke, Senior Analytics Strategist, DAIN Studios Oy

19:55 Networking


You can register for the event by clicking this Eventbrite link.

For further information about the event, please email: majella.clarke@dainstudios.com