Shanjeeda Shafi

*** ***** ***** *****, ****, NC *7519, Phone: 984-***-****,

adj69a@r.postjobfree.com

Dynamic and Result-oriented SAS and R Programmer with extensive years’ experience covering all aspects of SAS and R processes – analysis, design, testing and validating, including advanced statistical methodologies and machine learning algorithms applied in Pharmaceutical and Biotech industries (Clinical Environment). Rich background in general linear models, categorical data analysis, survival analysis, multivariate analysis, design of experiments, longitudinal data analysis, randomized trial designs, clustering/classification methods and survey design and analysis, as well as development and QC of SAS programs to create listing, reports and creating dataset according to CDISC SDTM guidelines and documentation. Education

Ph.D., Mathematical Statistics 2020 University of Newcastle, Australia M.Sc., Statistics 2006 University of Dhaka, Bangladesh B.Sc., Statistics 2004 University of Dhaka, Bangladesh PhD Thesis Title- Machine Learning and Mixture Clustering Methods for Molecular Drug Discovery: Prediction and Characterisation of Druggable Drugs and Targets, Supervisor: Prof. Irene Hudson, Co-supervisor: Dr. Robert King.

Work Experience

Currently Freelancer Statistician ShanSTAT

• Provide statistical expertise for design, analysis and reporting clinical and scientific research studies.

• Evaluate data through SAS and R programmes and interpret into relevant statistics.

• Familiarity with CDISC/ Study Data Tabulation Model

• Provide ad hoc listing and reports for sponsor use.

• Expertise on predictive modeling.

02/2018-09/2020 Statistical Consultant (Remote-Part time) SARDI- Australia

• Establishing and operationalizing hypotheses, research questions and leading to tracking geographical origin of 2 quarantine fruit fly pests in 2018 outbreak via FAMD analysis (Factor analysis for Mixed data).

• Establish appropriate mathematical algorithms for microsatellite dataset.

• Mapping 6 fruit fly outbreak geographical region by analyzing homologous gene of interest via PCA analysis saving 20-billion-dollar agriculture industry.

• Preparing report for industry as demonstrated by securing in grant funding.

• Successfully identify the dominant pattern of 7 Mediterranean fruit fly by using statistical tools including one-way ANOVA with post-hoc Tukey HSD test and MANOVA and visualize this via Tableau.

07/2017-07/2018 Statistician/Research Officer (Part time) Biometry hub, Australia

• Performed statistical analysis (mixed model) in biological data to help investigator for purposes of breeding, agronomy practices and scientific research.

• Plan, execute, and finalize projects on time and within budget and scope objectives, including acquiring resources and coordinating efforts of research team members.

• Develop tests to analyst data sets using R or equivalent, and clearly highlight the algorithms/approaches taken and why.

• Applied PCA/ MCA/FAMD for visualization of biological data via R package Factomine R and used ggplot2 for report presentation.

02/2012-12/ 2019 Graduate Research University of Newcastle, Australia

• Applied visualization tools PCA, MCA and FAMD to investigate the region of chemical spaces in high dimensional chemical datasets by R package Factomine R.

• Applied machine learning algorithms such as recursive partitioning, support vector machine and naïve bayesian techniques via different R packages.

• Applied mixture-based Bayesian and non-Bayesian clustering techniques via different R packages in multidimensional drug dataset.

• Build predictive modeling via machine learning algorithm to address client preferences. 01/2006-06/2009 Data management officer ICDDRB, Bangladesh

• Designed survey research studies including questionnaire development, sample selection, checking survey results, statistical analyses and data reporting.

• Involved in maternal and neonatal health project and statistical report helps in the development of national policy.

• Consult one-on-one or in small groups to clarify statistical analyses and interpret results.

• Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.

PROFESSIONAL SKILLS

Technical skills

Clinical trial/Drug Design/Cheminformatics

• Extensive knowledge of SAS programming techniques and programs especially SAS 9.2

• Extensive knowledge of R programming (used different types of package Rmixmod, Depmixs4, Caret, Factomine R, mixAK, ggplot2, epiR, ROCR, mclustDA, bayesmix, mixtools, e1071, Rpart)

• Data visualization using SAS, Tableau and R

• Clinical Research, cheminformatic and genetic data analysis

• Statistical Documentation and Consolidation

• Advance statistical methodologies

Machine learning algorithms.

• Logistic regression

• Clustering/Classification/Discriminant

• Data visualization

• PCA\MCA\FAMD

• Predictive/Forecasting modeling

• Druglikeness/druggability modeling

• Bayesian clustering technique

• Hidden Markov Model

• Gaussian mixture model

• Markov chain monte carlo simulation

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