Actuarial analyst vs data scientist

Differences between actuarial analyst and data scientist duties and responsibilities

Actuarial analyst example responsibilities.

• Lead an experience study on morbidity assumptions to more accurately identify LTC rider risks.
• Lead actuarial intern on automating internal reports, help intern write SQL queries and VBA macros.
• Develop SAS programs to automate analysis correcting extant errors resulting from arduous manual processes.
• Evaluate capitation agreements between provider groups and manage care plans, including commercial and Medicare populations.
• Analyze GAAP financial statements including fair value assessment, shadow adjustments, embed derivatives and unlocking.
• Integrate rating factors and other data used for GLM motor pricing model by SAS, SQL.
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Data scientist example responsibilities.

• Update, maintain, and manage regional CRM database and records for customers, vendors, and suppliers.
• Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
• Lead the analysis in SAS for data integration of mortality data using meta-analysis integration methods.
• Implement a proximal stochastic gradient descent with a line search to fit a regularize logistic regression in Scala
• Perform cross-validation-test on linear regression model of data using scikit-learn.
• Develop python base statistical visualization to provide insights of fuzzy social media data.
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