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
Report job
