A dynamic Senior Biostatistician and Data Scientist seeks to bring an accomplished combination of education and experience to an industry-leading employer. 15+ years of experience in related data analysis, computer programming, and instruction roles for distinguished universities. Ph.D. in Biostatistics, with an M.S. in both Bio-Engineering and Applied Mathematics. Proficient in data management, mathematical modeling, grad/undergrad instruction, longitudinal/statistical analysis, project management, and more. Diligent and goal-oriented, with the skills, education, and hands-on experience needed to make an immediate impact as part of any fast-paced team.

Top Rates Plus - awarded to the top 3% of Upwork freelancers! Experienced Senior Statistical Programmer with over 8 years of expertise in clinical trials and pharmaceutical research across therapeutic areas including oncology, cardiology, dermatology, gastroenterology, neurology, hematology, Real World Evidence (RWE), peptides and vaccines studies. Strong leadership capabilities in coordinating programming activities and timelines across multiple studies in phases I-IV. Dedicated to maintaining data integrity and supporting efficient clinical trial operations. Proficient in the development of statistical computing environments and serving as a clinical trials subject matter expert (SME) for software development companies supporting clinical research solutions. For a detailed overview of my hands-on responsibilities and real-world contributions, please refer to the Employment section, which outlines how this expertise has been applied across clinical trial development and pharmaceutical research projects. I hold Bachelor of Data Science degree from the American University of Armenia. My educational background, combined with hands-on experience, has equipped me with a robust skill set and a deep understanding of statistical methodologies and programming languages relevant to the clinical trials domain. My technical skills include proficiency in: SAS Programming (Advanced Level Certified, see in the 'Certifications' section): • Advanced SAS/BASE, SAS, SQL, SAS/MACRO, SAS/GRAPH, SAS/STAT, SAS/PROC, ODS output • SAS Viya (cloud version), Integration with R and Python, SAS Visual Analytics • Arrays, Hash Objects, Advanced Indexing, Memory Management • Handling large and complex datasets with efficient I/O and parallel processing techniques • Advanced macro writing, debugging and dynamic code generation, nested and recursive macros • Git/version control tools R Programming: • Clinical packages - pharmaverse, admiral, sdtmoak, tfrmt, gtsummary, PKNCA • Data manipulation and transformation - tidyverse, dplyr, tidyr, purrr, stringr, lubridate, tibble (implicit), readr (implicit) • Data visualization - ggplot2, plotly, gtsummary (dual-purpose), gt, flextable, patchwork, cowplot • High-quality analytical reports - rmarkdown, knitr, quarto • Interactive dashboards and applications using R Shiny Python Programming: • Python core (data types, control flow, functions, modules), NumPy, pandas, SciPy. • Clinical data processing with pandas (joins, reshaping, group summaries, derivations comparable to SDTM/ADaM workflows). • Integration with SAS and R (reading/writing SAS datasets via pyreadstat, interoperability for QC and validation). • Data visualization and reporting (matplotlib, seaborn, Excel/CSV outputs, automated report generation). • Advanced data handling (vectorization, memory optimization, chunked processing, handling large datasets). • Statistical analysis in Python (descriptive statistics, hypothesis testing, regression, survival analysis using lifelines). • Validation and quality control frameworks (independent QC of SAS outputs, data consistency checks, audit-friendly logs). • Unit testing and code quality (pytest, structured logging, reproducible environments). • Metadata and XML processing (Define-XML handling, CDISC metadata validation using xml/lxml). Power BI & Business Intelligence: • Design and development of interactive Power BI dashboards for exploratory and operational analytics • Data modeling using Power BI semantic models, relationships, and star-schema concepts • Data transformation and preparation using Power Query (M language) • KPI development, filters, drill-downs, and slicers for executive-ready reporting • Integration with multiple data sources (CSV, Excel, SQL databases, APIs) • Performance optimization for large datasets (model size, relationships, DAX efficiency) • Secure sharing and collaboration using Power BI Service Project Management: Working with Jira, Scrum, GitHub Microsoft Office tools: Microsoft Word, Excel, PowerPoint, Access, Outlook Driven by a passion for continuous learning and a collaborative spirit, I am known for my easy-going demeanor and my ability to thrive in team environments within the clinical trials field. I approach each project with dedication and attention to detail, consistently delivering results that exceed expectations and contribute to the advancement of clinical research.

SAS consultant specializing in IFRS9 & IFRS17 regulatory implementations, SAS Viya 4, and risk reporting for banks and insurers. 4+ years delivering production-grade SAS solutions across some of MENA's largest financial institutions. Most SAS freelancers do one thing — write programs or run statistics. I cover the full lifecycle banks and insurers actually need: - Regulatory implementation — IFRS9 and IFRS17 on the SAS Solution: data-quality rules, staging/ETL alignment to input specs, model-run debugging, and reporting redesign. - Platform deployment & administration — SAS Viya 4 on Red Hat OpenShift, SAS 9.4 on RHEL, Ansible installs, LDAP integration, hotfixes/patches, and environment hardening. - Automation & development — Base SAS, Macros, DI Studio ETL, Stored Process batch chains, and SQL pass-through. - Reporting & BI — SAS ODS/EXCEL, SAS Visual Analytics, and Power BI dashboards for risk, fraud, and monthly bank reviews. Recent work: redesigned the IFRS9 implementation and reporting layer for a top-tier MENA bank, deployed SAS Viya 4 on OpenShift, automated an IFRS9 batch chain with Stored Processes, and ran a full security-remediation pass on a production SAS 9.4 environment (Log4j, end-of-life components, SSH hardening) with an audit-ready register. I hold the SAS Base Programming Specialist certification and an engineering degree in computer science (BI specialization). I work fluently in English and French. Need someone who can implement the regulation, stand up the platform, AND ship the report — not just one piece? Let's talk.

Your marketing spend is scaling, but your profit margins aren't following. Your teams are drowning in spreadsheets, and your current dashboards create more questions than they answer. 𝗜 𝗳𝗶𝘅 𝘁𝗵𝗶𝘀. As a Data Scientist and Marketing Analytics Expert with over 12 years of experience, I help business owners stop guessing and start scaling. With an M.S. in Statistics (Texas A&M) and deep expertise in Tableau, SQL, and R, I build the automated data pipelines and executive dashboards that leadership teams actually use to drive revenue. I don't just hand over charts, I treat your marketing like a highly optimized production line to eliminate waste and maximize profit. 🎯 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 (𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗘𝘅𝗽𝗲𝗰𝘁):   1. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗧𝗮𝗯𝗹𝗲𝗮𝘂 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀: Clean, interactive dashboards that put profit-driving KPIs front and center (CAC, LTV, ROAS, Payback Period, Conversion).   2. 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗦𝗽𝗲𝗻𝗱 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Aligning your marketing data with profit metrics, historically delivering 15–30% ROI improvements for my clients.   3. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀: Replacing manual, error-prone spreadsheet work with automated SQL/R data workflows that speed up decision cycles by 20–50%.   4. 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 & 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: Uncovering your most high-value customers and most profitable acquisition channels using advanced statistical analysis. 🏆 𝗪𝗵𝘆 𝗖𝗵𝗼𝗼𝘀𝗲 𝗠𝗲?   • 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗘𝘅𝗽𝗲𝗿𝘁: 5+ years of delivering 5-star results on Upwork.   • 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗥𝗶𝗴𝗼𝗿: M.S. in Statistics ensures my models and insights are mathematically sound, not just superficial vanity metrics.   • 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗣𝗮𝗿𝘁𝗻𝗲𝗿: I don't just build what you ask for; I advise on what you actually need to hit your growth targets. 🛠️ 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 & 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀:   • 𝗕𝗜 & 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Tableau (Dashboard Design, Blending, Automation, Interactivity)   • 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: R, SAS, Predictive Modeling, Linear Regression, Forecasting, Cohort Analysis, Propensity Modeling   • 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: SQL, ETL Pipelines, Automated Reporting, Data Modeling, AWS, Athena, PostGres, Make   • 𝗗𝗼𝗺𝗮𝗶𝗻 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: Marketing Analytics, E-commerce, Manufacturing, Campaign Reporting Ready to stop guessing and scale with clarity? Send me a message or book a consultation to discuss your current data setup and how I can turn your analytics into a profit center.

I am an experienced Statistician and Biostatistician with 6 years of expertise in R and SAS, specializing in statistical analysis, data modeling, and research reporting. I support academic research, clinical studies, and thesis work by performing robust statistical analyses, preparing high-quality results, and guiding clients through methodology, interpretation, and presentation. I also provide complete statistical support for paper publications, including analysis, tables/figures, and responses to reviewer comments. My goal is to deliver clear, reliable, and reproducible results that help clients achieve strong research outcomes and informed decision-making. Statistical Analysis & Methods: Descriptive Statistics & Inferential Statistics Parametric and Non-Parametric Tests Normality Testing & Normal Distribution Analysis Missing Data Handling & Imputation Techniques Odds Ratio, Risk Ratio & Effect Size Estimation Survival Analysis (KM, Cox Model) Sample Size Calculation & Power Analysis Statistical Analysis Plans (SAP) Randomization Methods (Block, Stratified, Simple) Bayesian analysis Tools & Programming: R, SAS, SPSS Data Cleaning, Validation & EDA Reproducible Reporting (Markdown, Scripts, Automation) Research & Clinical Analytics: Clinical Data Analysis (Phases I–IV) Thesis, dissertation & publication statistical support

Excel (Macros-VBA), SQL, Access, PowerBI, Google Sheet expert, with more than 20 years experience in: data analysis, ETL, data visualizaton, improvement of processes, dynamic applications, covering: Accounting, Pricing, HR, Time Sheets, Invoicing, CRM, Finnancial Issues, Business Plannig, Data Consolidation, PDF Generation, Administrative tasks, etc..

I am an Economist, Researcher, and Data Analyst with over 7 years of professional experience in statistical and econometric analysis using Stata, SPSS, EViews, RStudio, AMOS, GRETL, SAS, JAMOVI, and Excel. I provide comprehensive research support across all stages of a project, including introduction, literature review (conceptual review, theoretical review, and empirical review), methodology, data analysis, discussion of findings, conclusion, and recommendations. With 4 peer-reviewed publications available on my Google Scholar profile, I bring strong expertise in quantitative research, econometric modelling, statistical analysis, and academic writing. I support students, researchers, businesses, and organizations in building solid research frameworks, defensible methodologies, and clear, evidence-based interpretations. Here is a comprehensive list of the econometric, statistical, biostatistical, machine learning, causal inference, survey, and diagnostic techniques I have employed: Econometric Methods Linear Regression Models • OLS • Multiple Linear Regression • Weighted Least Squares (WLS) • Generalized Least Squares (GLS) • Feasible Generalized Least Squares (FGLS) Panel Data Models • Fixed Effects (FE) • Random Effects (RE) • Hausman Test • Breusch-Pagan LM Test • Two-Way Fixed Effects (TWFE) • Driscoll-Kraay • Cluster-Robust • Panel-Corrected Standard Errors (PCSE) Dynamic Panel Models • Difference GMM • System GMM • Two-Step Robust System GMM • Windmeijer Correction • Instrument Reduction Techniques • Hansen Test • Sargan Test • AR(1) and AR(2) Serial Correlation Tests Instrumental Variable Models • 2SLS • 3SLS • IV Regression • Endogeneity Testing Causal Inference Methods • Difference-in-Differences (DiD) • Staggered DiD • Dynamic DiD • Event Study • Propensity Score Matching (PSM) • Treatment Effects Models • Placebo Tests • Falsification Tests • Heterogeneity Analysis Time Series Econometrics • ARIMA • ARMA • VAR • VECM • ECM • Unit Root Tests (ADF, PP, KPSS) • Cointegration Analysis • Granger Causality • Impulse Response Functions • Forecast Error Variance Decomposition Volatility Models • ARCH • GARCH Regression Models for Limited Dependent Variables Binary Outcome Models • Binary Logistic Regression • Binomial Logistic Regression • Probit Regression Multinomial Models • Multinomial Logistic Regression • Multinomial Probit Ordered Outcome Models • Ordered Logit • Ordered Probit Count Models • Poisson Regression • Negative Binomial Regression • Zero-Inflated Models Biostatistics and Clinical Research Methods Comparative Tests • Independent Samples t-Test • Paired Samples t-Test • One-Sample t-Test • Mann-Whitney U Test • Wilcoxon Signed-Rank Test • Kruskal-Wallis Test • Friedman Test Categorical Data Analysis • Chi-Square Test • Fisher's Exact Test • McNemar Test Clinical Study Analysis • Cohort Studies • Retrospective Observational Studies • Longitudinal Studies • Repeated Measures Analysis Survival Analysis • Kaplan-Meier Survival Curves • Log-Rank Test • Cox Proportional Hazards Regression • Competing Risk Models • Time-to-Event Analysis Clinical Trial Analysis • 2×2 Cross-Over Design Analysis • Carryover Effect Testing • Period Effect Testing • Sequence Effect Testing Mixed Effects Models • Linear Mixed Models • Generalized Linear Mixed Models (GLMM) • Random Effects Models • Repeated Measures Mixed Models Propensity Score Methods • Propensity Score Matching • Covariate Balance Diagnostics • Sensitivity Analysis Survey and Questionnaire Analysis Reliability and Validity • Cronbach's Alpha • Composite Scale Construction • Reliability Analysis Survey Analysis • Frequency Analysis • Cross-Tabulations • Weighted Survey Analysis • Survey-Weighted Logistic Regression • Survey-Weighted GLM Psychometric Methods • Exploratory Factor Analysis (EFA) • Confirmatory Factor Analysis (CFA) • Principal Component Analysis (PCA) Structural Equation Modeling (SEM) • Mediation Analysis • Moderation Analysis • Path Analysis Multivariate Statistics Dimension Reduction • Principal Component Analysis (PCA) • Exploratory Factor Analysis (EFA) • Confirmatory Factor Analysis (CFA) Classification and Segmentation • Cluster Analysis • Hierarchical Clustering • K-Means Clustering Association Analysis • Correlation Analysis o Pearson o Spearman o Kendall Educational, Psychology, and Social Science Methods Group Comparisons • ANOVA • Repeated Measures ANOVA • ANCOVA • MANOVA • MANCOVA Effect Size Estimation • Cohen's d • Odds Ratios • Relative Risks • Hazard Ratios Data Quality and Missing Data Techniques • Multiple Imputation (MI) • Complete Case Analysis • Missing Data Diagnostic • Outlier Detection • Winsorization • Data Harmonization • Variable Construction • Data Validation For every project, I can also provide the relevant codes, syntax, or do-files to help you replicate the results and understand the analytical process. Let’s connect. Your project deserves clarity, precision, and data-driven guidance.

I am an epidemiologist and biostatistician with over five years of applied experience conducting statistical analyses for clinical, public health, and health services research. I currently work full-time as a biostatistician at UCLA Health, supporting physician-led and investigator-initiated studies across multiple medical specialties. My training includes an MPH, an MS in Data Analytics, and formal graduate-level coursework in biostatistics and epidemiologic methods. I specialize in the design, analysis, and interpretation of observational and clinical data, with particular strength in causal inference, regression modeling, and large-scale healthcare datasets. I have extensive experience working with electronic health records and claims data (including longitudinal, high-dimensional datasets), and I routinely translate complex statistical results into clear, decision-relevant outputs for clinicians and research teams. Technical expertise includes: - Statistical modeling: logistic, linear, Cox and competing risks models, mixed-effects models, generalized estimating equations - Causal and quasi-experimental methods: propensity scores (matching/weighting), difference-in-differences, instrumental variables, regression discontinuity - Study design and power/sample size calculations - Machine learning for prediction (with an emphasis on interpretability) - Reproducible analysis pipelines and reporting Tools: SAS (Base and Advanced 9.4 certified), R, Python, SQL I frequently support projects end-to-end, including analytic plan development, data cleaning and cohort construction, model implementation, results interpretation, and preparation of tables and figures for manuscripts, grant applications, and regulatory or internal reports. I am also available for targeted statistical consulting, code review, and methodological troubleshooting. I am particularly well-suited for clients who need rigorous, publication-quality biostatistical support and clear communication—not black-box analyses. If you are working with health, clinical, or epidemiologic data and need a statistician who understands both methodology and applied constraints, I can help.

Hello, I am a professional Data Analyst and Statistician with over seven years of experience in data analysis and more than five years of experience teaching statistics, including Basic and Applied Statistics. I help businesses, researchers, students, and organizations transform complex and unstructured data into accurate, meaningful, and actionable insights. My work covers the complete data analysis process, from data collection and cleaning to statistical modeling, visualization, interpretation, and professional reporting. My Core Services ✔ Data Cleaning and Wrangling – Identifying missing values, duplicates, inconsistencies, outliers, and data-entry errors ✔ Exploratory Data Analysis (EDA) – Examining distributions, trends, relationships, and underlying patterns ✔ Statistical Analysis and Modeling – Applying descriptive, inferential, regression, multivariate, and advanced statistical techniques ✔ Research and Survey Data Analysis – Analyzing questionnaires, experiments, clinical studies, and academic research data ✔ Data Visualization and Dashboards – Developing interactive dashboards, charts, graphs, and management reports ✔ Predictive Analytics and Forecasting – Building machine-learning and time-series models to support future planning ✔ Results Interpretation and Reporting – Presenting technical findings in clear, professional, and understandable language ✔ Data Validation and Quality Assurance – Ensuring accuracy, consistency, completeness, and reliability across datasets Tools and Technologies Statistical and Analytical Software: R, Python, SPSS, Stata, SAS, EViews, and Minitab Python Libraries: pandas, NumPy, statsmodels, scikit-learn, and Matplotlib Data Visualization and Business Intelligence: Power BI, Tableau, Looker Studio, Excel Dashboards, Zoho Analytics, Metabase, and Apache Superset Data Management and Cleaning: Advanced Microsoft Excel, SQL, Power Query, and OpenRefine Machine Learning and Forecasting: Regression, classification, clustering, predictive modeling, and time-series forecasting Survey and Research Platforms: REDCap, KoboToolbox, Google Forms, and Microsoft Forms Cloud and Collaboration Tools: Google Sheets, Microsoft 365, Jupyter Notebook, GitHub, and Google Colab I have experience working with academic research, business datasets, survey data, educational data, agricultural and climate data, and healthcare-related datasets. I can also provide well-documented analysis, reproducible code, publication-quality tables and graphs, and reports suitable for theses, research papers, presentations, and management decision-making. My priorities are: ✔ Accurate and reliable analysis ✔ Clear communication and regular progress updates ✔ On-time delivery ✔ Confidential handling of client data ✔ Practical and actionable recommendations ✔ Complete client satisfaction Whether you need data cleaning, statistical analysis, machine-learning models, an interactive dashboard, survey analysis, forecasting, or a professionally written analytical report, I am ready to support your project. Please feel free to contact me to discuss your requirements. I look forward to helping you turn your data into valuable insights. Best regards, Ghulam Murtaza

🔥 I turn raw data into decisions : 12+ years of analytics at GlaxoSmithKline and across the pharma industry. MSc Bioinformatics, Imperial College London. 🟢 My Superpower I'm your "data translator"; I speak Python, R, and SQL fluently, but I translate everything into insights your stakeholders will actually understand and act on. 💼 Who I Help Pharma companies, healthcare orgs, and business leaders tired of spreadsheets that tell them nothing and dashboards that confuse everyone. 😏 Why Clients Hire Me - 12+ years across 3 countries (UK, France, Morocco) - Dashboards at GSK that increased decision-making speed by 20% - Automated reporting that saved teams 40% of their time - Statistical analysis that drove 15% regional sales growth 🤯 What I Do - Build Power BI & Tableau dashboards your team will actually use - Design surveys that produce actionable insights, not just charts - Automate reporting with SQL & Python so you focus on strategy - Rigorous statistical analysis (SPSS, JMP, SAS, R) 🧩 Core Skills ✔ Power BI, Tableau, R Shiny, MicroStrategy ✔ Python, R, SQL, SAS ✔ SPSS, JMP, Minitab, Statistical Modeling ✔ English (Fluent) | French (Native) | Arabic (Native) ✅ MSc Bioinformatics : Imperial College London | BSc Mathematics University of Leicester 👩‍💻 If you want someone who turns data chaos into clear decisions, let's talk.