Yes, here is the updated version -- I added many details about MEAN stack and the REST data apps, which are most recent skills and experiences (and most relevant to the direction I'm trying to head to). I know that people would notice most of my experience is in healthcare (claims data) with SAS, I'm still very good at that but I'm just trying to move on (I was earning top rate, which is too expensive, plus many young graduates are coming into that, so I have to move on).
Long time experience with SAS and R, certified for both SAS®9 Base and Advanced programming. Proficient in macros, SQL, ODS and hash. Very familiar with statistical procedures(Procs) in both SAS/base and SAS/stat.
Hands on experience with healthcare data and analytics – medical and pharmacy claims, electronic medical records, etc. Experience of serving pharmaceutical clients on phase 3 (clinical data, regulatory compliance, ICH and CDISC, etc.) and 4 studies (disease specific cohort/registry, MarketScan, etc.).
04/2016 – present: Independent projects of full stack data apps development, using public accessible data released by government (FDA for drugs, Medicaid for cost, CMS for providers info). Apps based on Node.js and deployed with nginx reverse proxy, sample app: http://hendashuju.com/HouseholdPrescribedMedicines/ (For example, query drug Effexor, NDC code 0008-0833-21).
10/2014 – 03/2016: Sr. Informatics consultant, Aetna Inc. (remote, contract through procurement)
Working with the Innovation Labs to provide data and analytics support, developed showcase project for evaluation of disease management programs from scratch, work concerns db2 data warehouse on Netezza, propensity score matching and predictive modeling of healthcare outcomes. The matching routine developed from pilot projects adopted by other domains of the corp.
06/2013 – 12/2013: Consultant, Connolly Healthcare. (contract through agency)
This is a very unusual arrangement: I was hired to test the methods that I developed for identifying errors in medical claims with the auditing department (“prove the concept” in their words). The methods were first developed using SAS, then redeveloped using R (to make it ready for software development), and finally implemented using Access and delivered using Excel. The testing results were very satisfactory – much better than myself was anticipating.
(During this work, I was away in October for two weeks, back to China for my kid's immigration visa interview, the interview did not go through because we were not prepared to bring the full set of required documents. After finishing this work, I went back to China again for re-interview, and finally brought the kid back on 03/14, 2014, and started full time looking since then.).
05/2012 – 02/2013: Consultant, Blue Cross Blue Shield of Massachusetts
Conduct analytical projects on membership data, medical and pharmacy claims data using Unix SAS and PC SAS 9.3, querying the data warehouse (~4,000 tables) upon internal requests for analytical support. Successfully developed very efficient programming approaches for these big healthcare data: using lately matured hash feature of SAS/Base to construct metrics and accurately identify newborns for delivery follow up after pregnancy; using Proc PRINCOMP of SAS/Stat to identify cancer conditions for disease management according to priority of clinical and financial outcome; using Proc LIFEREG to model membership gaps for justification of financial analysis; using Proc FASTCLUS to conduct cluster analysis to identify service episodes for medical cost analysis and detection of outliers.
01/2010-02/2012: Serving the two-year custody of my adopted child in China, in order to meet the requirement set by US immigration law, for the purpose of sponsoring him immigrating to US for family reunion. Besides taking care of the child, I try to stay current and alert with healthcare issues (i.e: detection and prevention of fraudulent healthcare claims), and keep polishing my skills in healthcare data structure, statistical analysis, SAS and R programming, staying prepared for job after returning to US.
07/2006-12/2009: Biostatistician, Humana Inc. This is a nation-wide medical insurance company with everyday contact to all-spectrum business matters of healthcare, as a biostatistician of its R&D group, I work on outcomes research based on claims data, to support internal business decision, as well as to serve external clients mostly for pharmacovigilance, clinical and scientific investigation.
I was the first biostatistician hired into the team, which gave me the opportunity of being the main contributor to creating the analytical process, establishing quality control standards, and setting up communication norms for deliverables including detailed documentation. I rocked off all the difficulties in this work flow, and made it a smooth and efficient process, with numerous studies completed that cover inquiries from health economics to medication adherence.
I also applied some of the latest methodology of confounding control for outcomes research: general estimating equations, multiple imputation, instrumental variables, inverse probability weighting, and g-estimation, etc.
All these work were conducted using Unix SAS, SAS Enterprise 4.3 and PC SAS, mostly the SAS/Base, SAS/Stat and SAS/ETS packages, with a strong emphasis on Proc SQL for querying the organization-wide electronic data warehouse (ETW) on Oracle and Microsoft SQL Server, and SAS data steps in combination to Proc CORR, Proc FREQ, and Proc PROC UNIVARIATE (in SAS/Base) for numeric quality control of analytical process, Proc LOGISTIC for logistic regression, Proc GLM for general linear regression, and Proc PHREG for survival analysis and conditional logistic regression.
03/2005-06/2006: Biostatistician, Cardinal Health, Inc. This is a major corporation in medical devices, supplies and logistics. As a biostatistician in its medical quality division, I was working on hospital mortality and hospital acquired infection, serving the purpose of outcome evaluation for medical quality assessment. The entire work was in the context of “Pay for performance” program of the client, trying to identify critical factors that affected hospital and provider performance. I had direct communication with the client.
This is my first contact to real healthcare data in general, and hospital data in particular. Experience at this position brings me real situation for applying statistical analysis and modeling, as well as SAS programming.
In this position, I was using Proc SQL in combination to data steps for data query, Proc CORR, Proc FREQ and Proc UNIVARIATE for analysis and analytical quality control, and Proc REPORT, TABULATE, SUMMARY for reporting and analytical communication.
2000-2004: Research Associate, Harvard School of Public Health. As a doctoral student working on thesis, I also worked for this job, responsible for management and analysis of genotype and diet data. I was using SAS as the primary analytical tool, and established my technical strength in this process. Because I was also involved in many other research activities, I was also experienced with Stata, R, the Linux operation system and script programming with Perl, Sed and Awk, etc.
1995-1998: Visiting Scholar, Joslin Diabetes Center. This is my first job in the U.S, conducting research on genetics of diabetes mellitus, with extensive bench work and applications of specialized software, as well as SAS. The research I was conducting led to findings of certain mutations that caused subtypes of type 2 diabetes; these results were published in academic journals.
1992-1995: Instructor, Beijing Medical University, Beijing, China. This is my last job in China, which is a teaching job of medical genetics.
BS, Hunan Normal University, Changsha, China. Major in Biology, 1984.
Master's, Hunan Medical University (merged to Central South University in 2000), Changsha, China. 1987.
Sc.D, Harvard School of Public Health, Boston, MA. Concentration in population genetics, minors in epidemiology and nutrition, 2005.
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Status in US: Citizen by naturalization.
References: Available upon request.
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