Yicheng Fan

* ***** ****, *** * • Buffalo, NY ***50

716-***-**** (cell) • acozqp@r.postjobfree.com

SPECIALTIES:

• Experienced in data analysis with strong knowledge in statistics and proven ability of providing

effective data to business leaders for them to manage the business more efficiently ;

• Results-oriented problem solver with skills at evaluating options and generating solutions;

• Always committed to team environment dynamics with the ability to contribute expertise and

follow leadership directives at appropriate times;

• Excellent computer skills in SAS(macro, sql, REG procedure, Mixed procedure, etc), R(PCA,

Clustering, PGM, etc), Monolix(population approach for PK/PD models), Python, Microsoft

Office;

• Excellent written and verbal communication skills in both English and Chinese;

WORK EXPERIENCE:

SUNY-Buffalo Buffalo, New York

Biostatistics Department, MA Candidate August 2012 – December 2014

Working as teacher assistant to be responsible for a master level course in homework assignments,

evaluation and necessary communications with the students;

Assisting my professor in a variety of tasks to improve his work and research efficiency.

• PPDAI-Microfinance company Shanghai, China

Risk Analyst December 2011 July

2012

Extracted and then analyzed the data from the credit system to create a business forward looking model

that estimated the business growth from potential clients. This business mode included thorough

analysis with “what if” in all aspects and potential possibilities impacting the entire business. It was

widely and successfully used by the financial and operating management teams in PPDAI.

Developed system modules that

• conducted credit system analysis to calculate client credit scores for the loan

applicants;

• implemented microfinance interest rate and overall income rate for investors;

• evaluated the effect of the credit system used for the collection department.

• China Securities Co., LTD Shanghai, China

• Composition Instructor August 2011 - November 2011

Operated stock exchange according to the will of senior clients.

Studied and Interpreted new stock and bonds policy like “selling stock short” to clients.

EDUCATION:

• SUNY-Buffalo, Master of Art in Biostatistics August 2012-Feb 2015

GPA: 3.84

Special recognition awards received in Autumn 2014

Certification received for SAS Certified Advanced Programmer for SAS 9 in November 2014

Certification received for SAS Certified Base Programmer for SAS 9 in September 2014

• Shanghai University., BS in Mathematics September 2007 – July

2011

PROJECTS:

Comparison of methods regarding multiple linear regression model with missing value

Examined the results from forward regression model selection method in SAS and analyze the algorithm

of this procedure to find the reason why listwise deletion occurs under this settings.

Devised a macro based forward model selection method based on forward selection algorithm.

Checked the accuracy, stability and reliability of this new method using multiple linear regression model

with relatively random missing values within each independent variable.

Produced results from multiple imputation under the same settings with MCMC approach.

Compared three methods by simulating data from normal distribution with classified missing percentage

and model coefficients. Corresponding results are presented in professional tables.

Forecasted potential challenges when applying this method for practical use in real world.

Empirical Likelihood Ratio Tests Based On Linear Regression

Devised a way to combine the empirical likelihood ratio tests with linear regressions

Studied the best number of constraints for linear regression model where we obtain the best power and

appropriate type one error with fixed sample size and data distribution

Interpretation of ANOVA Models for Microarray data using PCA

Devised a way for ANOVA Analysis of microarray data and Selecting genes based on P values

Improved the interpretation of the results from ANOVA on large microarray datasets by applying PCA on

the individual variance components

Visualized the interaction effect using biplot.

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