Principal Actuarial Data Scientist

Safe-Guard Products International LLC•Atlanta, GA

8d•Hybrid

About The Position

Safe-Guard’s Risk Department is expanding and adding a new Principal Actuarial Data Scientist role within the Enterprise Analytics team. The position of Principal Actuarial Data Scientist is a professional-level position that requires the application of advanced mathematical, statistical, and actuarial theory to the analysis of insurance risk, claims, and pricing. In this role, you will independently formulate the mathematical and actuarial approach to complex business problems, build and validate the underlying quantitative models, and oversee their application in production. You will be responsible for a wide variety of analytical tasks and will be responsible for leading a small team of Data Engineers and Data Analysts.

Requirements

4+ years working in analytical role (e.g., data scientist, data analyst, etc.)
Proven track record of developing and deploying analytical solutions
Foundational understanding of common data science techniques such as logistic regression, decision trees, clustering, A/B testing, design of experiments, hypothesis testing, and neural networks
B.S. in mathematics, computer science, statistics, engineering, or equivalent
Expert proficiency in SQL, Python, and Git
Strong written and verbal communication skills
Experience leading or mentoring Jr. Data professionals

Nice To Haves

M.S. in mathematics, computer science, statistics, engineering, or equivalent

Responsibilities

Formulating and applying mathematical, statistical, and actuarial models — including regression analysis, stochastic and probabilistic modeling, classification techniques, clustering, hypothesis testing, and neural network-based methods — to quantify and predict risk and profitability outcomes
Designing and conducting statistical experiments (A/B testing, design of experiments) to test hypotheses and validate model assumptions
Translating business and actuarial risk questions into formal mathematical and statistical problems, and developing the analytical frameworks and algorithms required to solve them
Building, validating, and monitoring the statistical performance of predictive models supporting claims and pricing analytics, ensuring mathematical and actuarial rigor
Applying mathematical and computational methods, using SQL and Python, to extract, structure, and analyze large datasets in support of quantitative and actuarial modeling work
Advising cross-functional partners in Claims, Legal, Sales, and IT on the mathematical and statistical soundness of analytical and AI/machine learning solutions
Serving as the technical authority on statistical methodology, actuarial modeling standards, and mathematical model design within the data science/ analytics function.