ahmad k.

Statistician & Data Scientist with an MSc in Statistics for Data Science. I help researchers and businesses turn complex data into defensible statistical results, predictive models, and clear decision-ready insights. My work covers statistical analysis, data analysis, biostatistics, machine learning, predictive modeling, research analytics, data cleaning, ETL, dashboards, and reproducible reporting using R, Python, SPSS, SAS, SQL, Excel, and Power BI. Statistical Analysis: hypothesis testing, regression, ANOVA/ANCOVA, non-parametric methods, effect sizes, confidence intervals, survey analysis, time-series analysis and research support. Data Science & Machine Learning: classification, clustering, predictive modeling, feature engineering, model validation, scikit-learn and TensorFlow/Keras. Data Analysis & Automation: Python/pandas, SQL, Excel, data cleaning, transformation, ETL, quality checks and reproducible workflows. Visualization & Reporting: Power BI, ggplot2, Matplotlib, R Shiny, dashboards and clear stakeholder-ready reporting. I focus on selecting the right methodology, validating the analysis properly, and explaining the results clearly—not simply generating code or output tables. R Packages: tidyverse, tidymodels, dplyr, ggplot2, caret, randomForest, glmnet, xgboost, nnet, lme4, forecast, data.table, readr, stringr, Shiny, Quarto, R Markdown and much more Python Packages: pandas, numpy, scikit-learn, statsmodels, matplotlib, seaborn, plotly, TensorFlow, Keras, PyTorch, XGBoost, LightGBM, CatBoost and much more Other Tools: SPSS, SAS, Minitab,Power BI, PASS, Microsoft Excel/Office, SQL, Power BI etc... I deliver clean, reproducible, and decision-ready analytics — from statistical modeling and survey analysis to machine learning pipelines and dashboards.