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Data Analyst | Spatial & Environmental Data | Python, R, SQL, QGIS
Mainz, Deutschland
Weltweit
M. Sc. Applied BioinformaticsÜber mich
Spatial and environmental data analyst with an M.Sc. in Applied Bioinformatics and seven years in groundwater ecology. Uses Python, R, SQL and QGIS to integrate monitoring, hydrochemical and land-use data and build reproducible, quality-controlled workflows.
Skills
BioinformatikBiostatistikExcel Pivot TablesR (Programmiersprache)PythonMultivariate AnalyseQgisSQL
Programming with Python, R and SQL
Proficiency in Python, R and SQL for data preparation, integration, quality control and analysis. Development of reproducible workflows and structured databases with rigorous quality control.
Statistical Analysis & Modelling
Application of regression modelling, multivariate statistics, hypothesis testing and predictive modelling to investigate environmental, spatial and clinical drivers. Experience with linear and logistic regression as well as TITAN2 for ecological change analysis.
GIS & Spatial Data Analysis with QGIS
Use of QGIS and PyQGIS to visualise, inspect and analyse georeferenced environmental and monitoring data. Preparation and examination of spatial context from large groundwater datasets across multiple regions.
Data Management & Integration
Data cleaning, data integration, data validation and maintenance of structured databases. Integration of biological, hydrochemical, monitoring, well-characteristic and land-use datasets from diverse sources.
Bioinformatics & Genomics
Development of statistical prediction models in R and Python for clinical genomics. Integration of clinical, sequencing and demographic datasets for modelling, exploratory analysis and visualisation.
Tools & Software
Experience with Bash, Snakemake, Conda, Git and macOS/Unix environments. Use of VS Code, RStudio, Jupyter, Excel, SPSS and PRIMER for data analysis and workflow management.
Reproducible Workflow Development
Development and maintenance of reproducible R/Python workflows for data preprocessing, quality control and analytical validation in both ecological and clinical research contexts.
Scientific Communication & Reporting
Presentation of findings to environmental organisations, practitioners and scientific peers through workshops and professional events.
Proficiency in Python, R and SQL for data preparation, integration, quality control and analysis. Development of reproducible workflows and structured databases with rigorous quality control.
Statistical Analysis & Modelling
Application of regression modelling, multivariate statistics, hypothesis testing and predictive modelling to investigate environmental, spatial and clinical drivers. Experience with linear and logistic regression as well as TITAN2 for ecological change analysis.
GIS & Spatial Data Analysis with QGIS
Use of QGIS and PyQGIS to visualise, inspect and analyse georeferenced environmental and monitoring data. Preparation and examination of spatial context from large groundwater datasets across multiple regions.
Data Management & Integration
Data cleaning, data integration, data validation and maintenance of structured databases. Integration of biological, hydrochemical, monitoring, well-characteristic and land-use datasets from diverse sources.
Bioinformatics & Genomics
Development of statistical prediction models in R and Python for clinical genomics. Integration of clinical, sequencing and demographic datasets for modelling, exploratory analysis and visualisation.
Tools & Software
Experience with Bash, Snakemake, Conda, Git and macOS/Unix environments. Use of VS Code, RStudio, Jupyter, Excel, SPSS and PRIMER for data analysis and workflow management.
Reproducible Workflow Development
Development and maintenance of reproducible R/Python workflows for data preprocessing, quality control and analytical validation in both ecological and clinical research contexts.
Scientific Communication & Reporting
Presentation of findings to environmental organisations, practitioners and scientific peers through workshops and professional events.
Erfahrung
Berufserfahrung5 - 10 Jahre
Freelancer seit2019
Sprachen
DeutschMutterspracheEnglischverhandlungssicherFranzösischgut
Projekthistorie
Integration of complex environmental, spatial and monitoring datasets with hydrochemical variables, temperature and indicators of anthropogenic pressure. Use of QGIS and PyQGIS to visualise and analyse georeferenced data. Development and maintenance of ecological databases and reproducible R/Python workflows. Application of multivariate statistics and TITAN2 to identify indicator taxa and evaluate drivers of ecological change. Presentation of findings at workshops and professional events.
Development of statistical prediction models in R and Python to investigate clinical outcomes and identify relevant risk factors. Integration of clinical, sequencing and demographic datasets for modelling, exploratory analysis and visualisation. Building of reproducible workflows for data preprocessing, quality control and analytical validation.
Integration of qPCR results with hydrochemical data, well characteristics and spatial land-use variables using R and QGIS. Used QGIS to prepare, visualise and examine the spatial context of data from 80 groundwater samples collected at 66 wells across six Australian regions. Applied multivariate statistics and linear and logistic regression to investigate potential environmental and spatial drivers. Final Grade: 1.2.