Looking to apply strong quantitative analysis, predictive modeling, and data engineering skills to turn complex data into actionable insights that optimize operations and support strategic growth.
Open to opportunities
Jack Kellison
@jackkellison
Quantitative Analyst with 6+ yrs in SQL, Python & financial modeling. Building cloud data pipelines & predictive models for executive strategy.
United StatesWhat I'm looking for
At CNO Financial Group, I model policy longevity and account exhaustion risks for Guaranteed Lifetime Income Annuity portfolios, quantifying benefit duration and exposure after account values reach zero.
I've supported annuity, traditional life, and interest-sensitive life valuation since 2020. My work has included portfolio liability analysis, dynamic forecasting, regulatory reporting under LDTI, and executive reporting on financial performance and portfolio risk.
I use SQL, SAS, Excel, predictive analytics, and cloud data warehousing to turn large policyholder and transactional datasets into reliable reporting and actionable insights.
I also partner with IT, Finance, and Strategy to improve data collection and analytics workflows. Outside of work, I cycled 3,740 miles with Journey of Hope to raise awareness and funds for people with mental and physical disabilities.
Experience
Work history, roles, and key accomplishments
Current
Modeled policy longevity and account exhaustion risks for Guaranteed Lifetime Income Annuity portfolios, quantifying benefit duration and exposure. Queried and structured large-scale policyholder databases using SQL and SAS to track cohort behavior and account value depletion timelines.
Conducted portfolio-level liability and valuation analysis, delivering data-driven insights on financial performance to executive management. Analyzed historical market trends and key behavioral assumptions using SAS to refine dynamic forecasting methodologies.
Designed and built cloud data warehouses to ingest, process, and optimize large volumes of transactional data, improving reporting efficiency and dynamic querying. Developed predictive and statistical models to adapt company reporting frameworks to new regulatory standards (LDTI).
Performed complex data analysis on interest-sensitive blocks of business to assess regulatory compliance and portfolio risk. Applied analytical software to translate raw transaction logs into executive dashboards and actionable business insights.
Education
Degrees, certifications, and relevant coursework
Purdue University
Bachelor of Science, Actuarial Science and Applied Statistics
Bachelor of Science in Actuarial Science and Applied Statistics with a minor in Management from Purdue University, College of Science.
Tech stack
Software and tools used professionally
Availability
Open to opportunities
Location
United StatesAuthorized to work in
Salary expectations
150k-200k USD
Job categories
Skills
SQLSASRPythonPredictive AnalyticsCloud Data WarehousingExcelVBAPower BITableaupredictive modelingTime Series AnalysisETLData WarehouseCohort AnalysisFinancial ModelingQuantitative Risk AssessmentA B TestingScenario TestingExecutive ReportingCross functional LeadershipRegulatory ComplianceProcess AutomationData ValidationBridges
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