Traditional Data Scientist

Required Skills & Experience:

10+ years of experience in data science, specifically within the insurance domain (e.g., health, life, P&C).
Strong proficiency in linear regression, logistic regression, and propensity score modeling.
Experience with tools such as Python, R, or SAS for data analysis and modeling.
Solid understanding of statistical theory and its practical application in real-world problems.
Familiarity with insurance business processes and KPIs is highly preferred.
Strong communication and data storytelling skills.
 

Nice to Have:

Experience working in regulated environments or with insurance compliance models.
Background in customer analytics, risk modeling, or marketing analytics.