Duties include: provide technical support and maintenance of pricing and underwriting tools to assist others understand underwriting case specific issues by answering technical questions; analyze and research actuarial projects partnering with project and management teams; assist with maintaining valuation system; evaluate, review, and estimate unpaid claims; develop statistical models for risk management, asset optimization, and pricing; research and develop reporting tools to track and monitor product performance against financial targets and objectives; work on special projects that require actuarial research and analysis which may involve partnering with other business areas both in and out of finance; develop reserve factors (to assist in evaluating, reviewing, and estimating unpaid claims); develop experience analysis reviews; contribute to product development and re-pricing initiatives; prepare routine reports and communicate research results to manager both in written format and orally; continually assess established training and work processes to identify areas for effectiveness and efficiency improvements, and contribute to operating effectiveness through information sharing, suggested process improvements and effective implementation of change; communicate trends and issues identified and proactively recommend resolutions to management; and develop reserve factors and analysis reviews; and prepare financial reports, tax returns, and state filings. Requirements: Master's degree (or foreign equivalent) in Actuarial Science, Mathematics, Data Science, Statistics, or a related field and completion of a university-level course, research project, internship, thesis, or six (6) months of experience in each of the following: • Actuarial models; • Java, Python, JavaScript or Bootstrap; • SQL, SAS, or R; • Machine learning, statistical analysis, and predictive modeling; • Software testing, quality assurance, and troubleshooting; • Data analytics on large data sets in healthcare, business, or retail sector; • Cloud components including cluster management; • Quantitative analysis techniques, including clustering, regression, and pattern recognition.