Senior Data Scientist, Advanced Analytics (Hybrid)

Safety National; Maryland Heights (MO); Hybrid; USD 117,000 - 151,000; Full time

Benefits offered by this job

Tuition reimbursement

Wellness benefits

Hybrid work schedule

Health, dental, vision insurance

401(k) match

Job summary

Safety National is seeking a Senior Data Scientist to join the Advanced Analytics team. You will tackle complex business problems by building predictive models, using ML to inform decision making, and delivering actionable insights across claims, underwriting and actuarial teams.

You will develop, deploy and validate models, ensuring data quality and regulatory compliance, while communicating findings to stakeholders and advancing data science capabilities across the organization.

Qualifications

• Master's degree required in a quantitative field.
• 6+ years experience as a Data Scientist with a focus on machine learning and predictive modeling.
• Strong SQL and cloud-based data warehouse experience (e.g., Snowflake).
• Excellent communication skills with the ability to explain complex technical concepts to diverse stakeholders.

Responsibilities

• Solve complex business challenges through advanced analytics and ML models.
• Collaborate with claims, underwriting, actuarial, and other teams to transform data into insights.
• Develop, deploy, validate, and optimize predictive models with robust data quality and reproducibility.
• Create impactful visualizations and communicate findings to diverse audiences.

Skills

Python

R

Scikit-Learn

XGBoost

TensorFlow

PyTorch

SQL

Education

Master's degree in Statistics, Mathematics, Actuarial Science, Computer Science, or another quantitative field

Job description

Safety National is seeking a Senior Data Scientist to join the Advanced Analytics team. You will tackle complex business problems by building predictive models, using ML to inform decision making, and delivering actionable insights across claims, underwriting and actuarial teams.

You will develop, deploy and validate models, ensuring data quality and regulatory compliance, while communicating findings to stakeholders and advancing data science capabilities across the organization.