Scoring Team Internship Milano

Scoring Team Internship
Milano
Lombardia, Milano

About Swiss Re

Swiss Re is one of the world's leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient.

We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime.

Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients.

This is possible thanks to the collaboration of more than 14, 000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking.

We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics.

In our inclusive and flexible environment everyone can bring their authentic selves to work.

**About the Role

In the field of insurance services, telematics data is becoming more and more important to improve the assessment of claims risk: from insurance companies covering personal vehicles to large fleet owners, everyone in this complex and varied market is interested in augmenting and improving the information available to better segment their portfolio.

A particular example in this field is the contextual risk: from an insurance perspective it is important that drivers take the safest route, and not the shortest or fastest one.

Our approach is to build and validate risk-based «map layers» to be used by routing and scoring solutions, to identify and provide paths minimizing the insurance risks.

**Objective

Swiss Re, together with a technological partner and leveraging on all the data sources available, wants to better understand and classify the risks of each individual driver or vehicle, as well as to provide risk-based solutions to multiple players in the automotive space:

- Map providers

- Fleet managers

- Car OEMs

- Insurers

Useful data in this regard potentially comprises multiple domains and sources:

- Base driving behavior detection (e. g.

time of the day)

- Features deriving from map enriching (e. g.

dangerous roads)

- Availability and activation of specific ADAS systems

- Distraction and fatigue detection

- Hazardous weather conditions

**About You

- Completed MSc in a STEM discipline;

- Experience with descriptive statistics and data modelling;

- Coding skills, preferably in Python or other scripting languages - fine at school level;

- Understanding of predictive statistics and Machine Learning methodologies.

We are an equal opportunity employer, and we value diversity at our company.

Our aim is to live visible and invisible diversity - diversity of age, race, ethnicity, nationality, gender, gender identity, sexual orientation, religious beliefs, physical abilities, personalities and experiences - at all levels and in all functions and regions.

We also collaborate in a flexible working environment, providing you with a compelling degree of autonomy to decide how, when and where to carry out your tasks.

LI-Hybrid