Sr. Pharmacy Data Analyst Resume Rockville, MD - Hire IT People

SUMMARY

Cancer research/data scientist, have interest in AI (machine learning, expert systems and neural networks) with deep learning applications in healthcare (clinical research/trial/diagnosis/prognosis); advanced analytics/big data analysis - predictive analytics that support clinical decision-making, patient stratification, population health/precision medicine.
Have interest in computational medicine, computational pathology, systems biology, bioinformatics and biostatistics.

AREAS OF EXPERTISE

Expertise in cancer risk assessment & prediction methods, using risk factors associated with developing cancers.
Skills in molecular diagnostics (PCR, NGS/DNA Microarray), clinical genomics/pharmacogenomics/radiogenomics.
Skill in software engineering/machine learning for big data analysis, and rule-based expert systems design (neural networks) for medical diagnosis/clinical decision making, computer-aided diagnostic (CAD) systems, DICOM, FHIR.
Skill in SAS: hypothesis testing steps, statistical inference and data mining (SVM, K-means clustering); and ability to build and train neural networks (CNN model) on databases for pattern recognition and image classification, using industry-standard software, tools/frameworks: Keras/TensorFlow, MATLAB, Caffe, NVIDIA DIGITS, R, Java/JESS.
Skill in the use of genome databases (GenBank, dbSNP, CaBIG, PharmGKB) & identify the genomics of a disease.
Expertise in inferential statistics analysis and probabilistic modeling (Monte Carlo stimulations, data uncertainty).
Skill in biostatistics/nutrition/toxicology/drugs as molecules-molecular biology & cellular processes linked to cancer.
Expertise in environmental/genetic risk factors involved in individual developing cancer; and analysis of these data, including genomics and data visualization methods (scatter plot, cluster, heatmap, Tableau for actionable insights.

PROFESSIONAL EXPERIENCE

Sr. Pharmacy Data Analyst

Confidential, Rockville, MD

Responsibilities:

Routinely extracts prescription drug information from pharmacy data sets (Rx claim/clinical data) on Netezza data warehouse for analytics and drug utilization reviews, summarization, insights use for decision making by directors.
Use SAS Enterprise miner for data analysis (abnormal trend) & advanced analytics (Rx count, claim counts, patterns utilization); built analytical model on drug level (predict values), evaluated model performance with team members.
Review spending and utilization of specialty drugs, e.g., cancer cost driver issues and claim frequency distributions.
Research on drug cost-effectiveness, why side effects plague most prescription drugs & increase in healthcare cost.

Data Analyst

Confidential, MA

Responsibilities:

Concern is that acrylamide, an environmental chemical (food contaminant that causes cancer in lab mice) may cause cancer in human.
Investigated acrylamide level in food and potential exposure to humans.
Conducted adult population food consumption survey (dietary intake/lifestyle of adult individuals), collected data was combined with acrylamide toxic levels discovered in processed food-toxicology lab data analysis (acrylamide levels were determined via HPLC) outcome was used for risk assessment/prevention recommendations (good diet and exercise).
Applied probabilistic model (Monte Carlo simulations, data uncertainty) for risk analysis & estimation of likelihood of adult exposure to acrylamide-a chemical carcinogen, reasonably anticipated to be a human carcinogen.
Used R statistical tool in this research project for data analysis/visualization, reviewed outcomes.
There were no defined correlations between acrylamide in dietary intakes and risk of developing cancer by adult individuals.

Adjunct Prof

Confidential, MD

Responsibilities:

Systems analyst

Confidential, VA

Responsibilities:

Adjunct Prof

Confidential, MD

Responsibilities: