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Capgemini is seeking a highly skilled and detail-oriented Jr Data Scientist to join our team to work for a top 10 US Insurance Carrier.
The team hiring for this position is responsible for building predictive model to solve business problems for personal lines products. The primary models they build are risk pricing models. This involves looking at historical policy, policyholder, claims data etc. to predict how much loss individual customer segments will generate. To support the pricing models and other predictive analytic needs for personal lines, they also build a variety of other models requiring techniques such as generalized linear models, neural networks, decision trees, cluster analysis, and multivariate statistical analysis. As a member of this team, you will collaborate with State Management, Underwriting, Actuarial, Claims and IT.
Utilizes basic knowledge to apply analytics and modeling techniques to improve business results. Performs routine assignments and leverages customer information and behavioral data to influence strategic business decisions while using analytics, multi-variate models, machine learning and data mining technologies. Assists in projects operationalizing business decisions while receiving some guidance and direction from more senior roles.
Our Client is one of the United States' largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.
Location: Brazil, Mexico
Requirements
Work Experience in This Field
Competitive compensation and benefits package:
About Capgemini
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2023.
https://www.capgemini.com/us-en/about-us/
The team hiring for this position is responsible for building predictive model to solve business problems for personal lines products. The primary models they build are risk pricing models. This involves looking at historical policy, policyholder, claims data etc. to predict how much loss individual customer segments will generate. To support the pricing models and other predictive analytic needs for personal lines, they also build a variety of other models requiring techniques such as generalized linear models, neural networks, decision trees, cluster analysis, and multivariate statistical analysis. As a member of this team, you will collaborate with State Management, Underwriting, Actuarial, Claims and IT.
Utilizes basic knowledge to apply analytics and modeling techniques to improve business results. Performs routine assignments and leverages customer information and behavioral data to influence strategic business decisions while using analytics, multi-variate models, machine learning and data mining technologies. Assists in projects operationalizing business decisions while receiving some guidance and direction from more senior roles.
Our Client is one of the United States' largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.
Location: Brazil, Mexico
Requirements
Work Experience in This Field
- Minimum Required: 1-3 years
- Minimum Required: Fluent
- Minimum Required: Masters
- Preferred: Masters
- Data Science
- Statistics
- Mathematics
- Computer Science
- Excel - Entry Level
- GIT - Entry Level
- Python - Entry Level
- SAS - Entry Level
- SQL - Entry Level
- Power BI - Entry Level
Competitive compensation and benefits package:
- Competitive salary and performance-based bonuses
- Comprehensive benefits package
- Career development and training opportunities
- Flexible work arrangements (remote and/or office-based)
- Dynamic and inclusive work culture within a globally renowned group
- Private Health Insurance
- Pension Plan
- Paid Time Off
- Training & Development
About Capgemini
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2023.
https://www.capgemini.com/us-en/about-us/
Key Skills
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c
ui
ai
ha
cis
git
esp
machine learning
neural networks
data mining
power bi
python
cloud
excel
rust
sql
sas
lan
pan
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- Posted
- Nov 14, 2024
- Type
- Full-time
- Level
- Entry
- Location
- São Paulo
- Company
- Capgemini
Industries
Non-profit Organizations
Primary
Secondary Education
Categories
Engineering
Information Technology
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