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Location: 

Bangalore, KA, IN

 

Analytics Specialist 

About Swiss Re

The Swiss Re Group 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. It anticipates and manages risk – from natural catastrophes to climate change, from ageing populations to cybercrime. The aim of the Swiss Re Group is to enable society to thrive and progress, creating new opportunities and solutions for its clients. Headquartered in Zurich, Switzerland, where it was founded in 1863, the Swiss Re Group operates through a network of around 80 offices globally. It is organised into three Business Units, each with a distinct strategy and set of objectives contributing to the Group’s overall mission.

 

About the Role and Team

 

The Digital and Smart Analytics (DSA) Service unit supports Swiss Re's business functions in generating insight from structured and unstructured data for their business and strategic initiatives (e.g., Big Data, Smart Analytics, Artificial Intelligence and growth programs).

 

Being part of the DSA service unit, the Predictive Modeling Solutions team builds and owns scalable end-to-end analytics solutions that enable data scientists to create and operate various kinds of analytics models, thus following ML/AIOps best practices.

 

The Opportunity:

Are you looking for applying your skills in Machine Learning and Artificial Intelligence with the goal of building innovative solutions?

 

To extend the existing Digital and Smart Analytics Solutions team we are seeking a motivated Data Scientist who will contribute in accelerating the deployment and improvement of analytics services in tight cooperation with peers, internal experts and business clients. In particular, the role will involve:

  • Generating business insight using data analytics and information visualisation methods to answer business problems in different (Re-) Insurance domains
  • Designing and developing analytics solutions to move towards data-driven innovation in alignment with business priorities and key targets
  • Driving enhancements of analytics products and services to improve business value and service quality according to business needs and industry standard methodologies.

 

Key Tasks:

  • Implement and deliver productive solutions in the areas of predictive modelling and geospatial modelling
  • Apply analytical methods and algorithms to build data products that streamline the process from data collection to insight generation
  • Validate, interpret and present data findings to both an expert and non-expert audience in tight collaboration with analytics consultants
  • Contribute in an agile team of data scientists and software engineers to develop and deploy data-driven solutions for various Insurance and Reinsurance business problems
  • Foster new data-driven approaches to generate business insights in order to address unanswered business problems in a proactive way
  • Build-up sustainable relationship with key business and IT stakeholders to become a trusted partner for the field of data analytics.

 

About You

 

Essentials:

  • 3+ years of professional experience
  • Bachelor's degree/Master Study/PhD (completed or near completion) in Data Science, Computer Science, Mathematics, Statistics (or equivalent)
  • Strong experience with Machine Learning in Python or R
  • Sound analytical & conceptual skills to understand key business needs and apply existing and novel analytics solutions to solve specific business problems
  • Knowledge on geospatial data analytics or strong willingness to acquire it
  • Excellent verbal and written English skills

 

Behavioural Competences:

  • Team player with a ‘can do’ attitude
  • Ability to work in an interdisciplinary and multi-cultural environment
  • High degree of independence and proactive working style
  • Ability to work on multiple priorities
  • Strong dedication to quality and timely delivery

 

Desired:

  • Understanding of (Re-) insurance services information needs
  • Experience in implementing productive solutions in an enterprise environment

 

 


Keywords:  
Reference Code: 88884