Senior Data Analyst with Predictive Modeling Expertise
Resume:
CHRISTOPHER LEISNER
*** **** **, ***. **, Port Chester, NY 10573
***********.*******@*****.***
SUMMARY:
Statistical analyst with concentration in loss prediction, risk prediction, and improving business processes
Expertise in creating actionable insights and impacts from data
Highly skilled in data analytics and requirement gathering
Excellence in data preparation, including acquisition, transformation, and cleaning
Proficiency in predictive modeling and data mining in R and SAS
Expertise in data visualization using R, SAS, Excel, and Power BI
Excellence in verbal and written communication, training, and mentoring
COMPUTER SKILLS:
R, Microsoft Office, Microsoft Power BI, SAS, SAS Enterprise Miner, and SAS Text Miner
QUANTITATIVE SKILLS:
Data science
Machine learning
Statistical Modeling
Data mining
Data visualization
Text mining
Data preparation
Technical writing
Mentoring and training
DEGREES:
M.S. Statistics
University of Illinois at Urbana-Champaign
Ph.D. Applied Mathematics
Purdue University
M.S. Electrical Engineering
Purdue University
B.S. Mathematics
State University of New York College at Brockport
CERTIFICATIONS:
Springboard – Foundations of Data Science Aug 2017
EXPERIENCE:
Senior Portfolio Analyst - Casualty, Swiss Re 11/19-11/25
Constructed dashboards to track trends in rate filings, securities class actions, multi-district litigations,
social inflation, and Workers’ Compensation claims severity
Constructed predictive models to forecast premium rate trends for various lines of insurance business
Compiled quarterly US Motor market intelligence reports with visualizations of metrics such as trends in frequency, severity, premium rates, exposure, fatality rates, injury rates, and court statistics such as verdict amounts; these provided insights into leading indicators that underlie loss trends and rate trends.
Compiled analyses to assess inflation risk to profitability for various lines of business
Created forward-looking view reports with short-term and long-term margin forecasts for Workers’ Compensation and Latin American Motor lines of business. These delivered views of key market trends to improve portfolio steering
Actuary, Atlas Financial Holdings 6/18-7/19
Constructed loss ratio predictive models in Guidewire to accurately price limousine, taxi, and paratransit vehicle fleet policies
Constructed subrogation model in Rapid Miner to estimate, at first notice of loss, the probability that given automobile claims would yield payment from subrogation
Constructed litigation propensity model in Rapid Miner to estimate, at first notice of loss, the probability that given automobile claims would be litigated
Constructed litigation severity model in Rapid Miner to estimate, at first notice of loss, the cost of litigating automobile claims
Trained Atlas employees to write SQL code
Verification Documents Administrator, Maximus (Temporary contract role) 8/17-2/18
Researched documents in health insurance applications submitted to NY State of Health marketplace
Verified accuracy of information from these documents
Edited health insurance applications to match information contained in documentation, when necessary
Generated notices to consumers who needed to take follow-up action
Trained new administrators (both one-on-one training and presentations to groups)
Business Performance Statistical Analyst, American Family Insurance 9/14-10/16
Constructed statistical model to predict losses and expenses for automobile and homeowner lines of business
Carried out time studies of claims workers’ time sheets to analyze their time allocation among tasks
Constructed attorney retention predictive model to predict which bodily injury automobile claims would have attorneys retained by claimants
Trained employees in the use of Hadoop cluster and text mining
Text mining to extract information from unstructured data, such as consumer sentiment from survey comments
Carried out adjuster time study to reduce loss expenses by increasing adjuster productivity without negatively impacting service
Built claim routing models to route auto physical damage and bodily injury claims to appropriate groups of claim handlers
Assessed performance of vendors who auction salvaged vehicles by constructing models to predict returns produced by vendors
Senior Actuarial Analyst, QBE Insurance 5/13-9/14
Built models to maximize profitability of QBE’s home inspection strategy; model scores homes according to likelihood that inspection will reveal underpricing or major hazards
Conducted credit study for personal auto and homeowner line of business to maximize return on QBE’s purchase of credit data; recommended purchase strategy based upon this model
Created model for scoring QBE insurance agencies to assess their future profitability potential
Led initiative to assess text mining tools for use in policy classification, claim classification, and creation
of new rating factors; trained team in the use of text mining tools
Constructed models to assess quality (as measured by prospective pure premium) of QBE’s lender-placed homeowner insurance portfolio
Constructed predictive models for pricing equine major medical and mortality coverage for livestock line of business
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