Marketing Manager at Data Science Conference / 4.0,
Our next guest is Saša Radovanović, he is a Data Science and CLM Team Leader at Telenor. He spoke at the conference about B2B offers on Mobile Apps, but for this interview we went further and asked about some hot topics such as GDPR, the use of Machine Learning in TelCo industry and the impact a data science community can have. Enjoy the interview :)
Telecommunication sector collects and processes a lot of data so Saša says that ML fits perfectly in this field. There are three major areas where it can be used - network experience, customer experience (call centers) and marketing (offers for clients). He thinks that machine learning can serve both customers and company well to match the needs of each side.
Simply put, there will be problems but companies will have to implement GDPR. GDPR stands for General Data Protection Regulation. Saša says that, at the core of this regulation is the user. It states that the final user has to know how the company is using its data. This regulation applies to all companies that are either operating in the EU or have clients in the EU. Our interviewee goes on to say that this will make things easier for companies who wish to expand or move to another country - they will no longer have to change their regulations according to a specific state but rather, by complying to GDPR they will be eligible to do business anywhere.
To have anything truly important happening in any field - you need critical mass, and the data science community is helping build critical mass. Saša thinks that such a community can help in sharing knowledge that this, in turn, will lead to data science being implemented in the real world. In this way, he goes on, we are building up on ideas that will create an environment where ML and AI (Artificial Intelligence) will be able to thrive and provide great value to all of us in the future.
Sasa is leading a team of data scientist and he sees two things that are really challenging. First, it isn’t easy to find a high quality data scientist, many people don’t have enough knowledge to be ready for the teamwork that is immediately necessary. Though, this isn’t a problem in itself - a person can be trained, but when you train a person you come to the second problem - there is a huge risk that now that a data scientist is trained and ready to work, they will leave to another company which will have greater benefits. To conclude, the greatest challenge is having the right people at the right time in the team, which can get really hard when you are working on big and important projects.
To watch the full interview, click here. Additionally, you may want to check out other interviews we did. Subscribe to our newsletter to hear about other interviews and many perks we offer to our subscribers like discounts for DSC 4.0 and many other conferences :)
Stay tuned and see you next week!
Danica Bozin is a physics student interested in doing her reaserch in complex systems applied to social phenomena. She's a data enthusiast with experince in marketing as she's currently working on DSC/4.0 as a marketing manager.