Yichen Liu

University of Cincinnati

**** *********** **, #****, **********, OH 45238

513-***-****

acdcxu@r.postjobfree.com

SUMMARY

Looking for a Business Analysis position utilizing statistical and financial knowledge with strong organizational and analyzing skills.

• Strongly skilled in regression modeling and analyzing.

• Excellent organizational skills - can handle multiple priorities.

• Critical thinker and meets deadline.

• Effective Interpersonal and teamwork skills.

EDUCATION

University of Cincinnati, Carl H. Lindner College of Business, Cincinnati, OH

MS-Business Analytics April 2014

• GPA: 3.7/4.0

• Relevant Coursework: data mining, simulation, optimization, statistical methods, probability modeling, and stat computing.

University of Cincinnati, McMicken College of Arts & Sciences, Cincinnati, OH

BA-Mathematics June 2012

• Major: Mathematics, tracking in the Actuarial Science.

• Relevant Coursework: Applied Statistics, ANOVA, Regression Modeling, Time Series, Reliable Survival Analysis, Finance, Economics.

• Financed 24% of education through UC global scholarship.

• Won the second prize in University of Cincinnati’s Calculus Contest in May, 2009.

RELATED EXPERIENCE

American Modern Insurance Group, Cincinnati, OH

American Modern Insurance Project January-April, 2013

Team Leader

1)Evaluate American Modern Insurance Group's pricing strategies on one of its insurance products, modular homes.

• Segment customers into groups based on their potential probability of loss counts.

•Assign different risk factor to each group of customers, make it convenient for AMIG to set up different price strategies for each

group.

2) Clean the raw data with SAS/SQL

• Due to the mistaken values in some variables, select the middle 90% data of those variables.

• Create the target variable "sum" by adding up the total claim counts for each customer.

3) Employed the classification tree in SAS Enterprise Miner to select relevant independent variables for the target variable.

• Selected 5 independent variables corresponding to the target variable "sum" from the total 57 associated variables.

4) Developed Zero-inflated negative binomial regression model to predict each customer's potential loss.

• Firstly considered generalized linear models which can deal with event counts dependent variable: Poisson and Neg-binomial

• Considered the fact that customers may or may not claim their loss to insurance company, the zero-inflated regression model was

introduced into GLM models.

• Employed SAS/STAT to estimated the parameters of each model, tested models by Voung test and Pearson Statistic, selected the

zero-inflated neg-binomial regression model as the best one.

• Used the final model to predict the expectated loss counts and claim counts for each customer.

5) Use the clustering analysis in SAS Enterprise Miner to segment all customers into groups.

• Clustered customers into 40 groups by predicted claim counts and loss counts using least square method.

• Sort the 40 customer groups by cluster's mean predicted claim counts and assigned each group with a risk factor.

6) Procedure involved: proc import, proc mean, proc freq, proc genmod, proc sgplot, proc transpose, macro.

SKILLS

• Computer and Programming Language: SAS (BASE/STAT/SQL/MACRO), R, Eviews, C Language, PASCAL, Mathematica, ITSM2000,

MS Excel VBA.

• Statistical and numerical method: Econometrics, Data Mining, Generalized Linear Models, Survival Analysis, Monte Carlo Simulation, and

Optimization

CERTIFICATION

• Passed one exam of Society of Actuaries (SOA)/Casualty Actuarial Society (CAS) and completed all three topics of Validation by

Educational Experience sponsored by SOA and CAS.

LEADERSHIP&ACTIVITIES

Volunteer for Kilgour School Carnival and 5K May 2011, 2012

• Set up games and booths for the Carnival Event.

• Helped register runners, handed out t-shirts, worked concessions, staffed the race route.

• Ran game and food booths.

Contact this candidate