Job Description

We are seeking a skilled Data Scientist to join our team, focusing on deriving business insights and driving data-driven decision-making. This position will help support predictive modeling needs across a growing portfolio of high-profile advanced analytics projects with the Strategic Analytics. As a key member of the team you will also play a role in advancing predictive modeling capabilities, enabling Arch to make better decisions. 

Responsibilities:

• Collaborate with experienced modelers to build predictive models and analytic solutions using Python ; apply techniques such as GLM, decision trees, GBM, NLP, and AI/LLM prompt engineering 
• Manipulate data using R or SQL Server; develop advanced ad hoc queries to investigate data anomalies and to summarize data for pattern detection 
• Develop Python or R functions and SQL stored procedures to automate recurring tasks 
• Create and maintain documentation associated with models 
• Assist in implementation and testing of models 
• Develop dashboards in Power BI to facilitate analyses that support modeling efforts or enable model usage 
• Monitor the performance and usage of models 
• Develop and implement predictive models and statistical analyses to forecast business outcomes. 
• Translate data insights into clear, actionable recommendations for stakeholders.

Qualifications

• At least 3 years’ predictive modeling experience in a professional setting, using tools such as Python or SQL 
• The ideal candidate will have experience working in the insurance industry 
• Exposure to AI/LLM, OCR, NLP and image analytics a plus 
• Detail oriented with strong organizational skills 
• Strong analytical skills 
• Excellent critical thinking skills in order to tackle complex data challenges 
• Comfortable working in a fast paced and highly collaborative global team 
• Ability to effectively communicate technical topics to different target audiences

Additional Information

BS in Mathematics, Statistics, Actuarial Science, Data Analytics, Computer Science, or equivalent