Data Analyst
About Candidate
Introduction:
The candidate is a seasoned data analyst with extensive experience in statistical modeling, data analysis, and cloud-based computing. Proficient in R, Python, SQL, and Bash, they specialize in analyzing quantitative and heterogeneous data to uncover meaningful insights. Their expertise spans IoT data analysis, time-series forecasting, hypothesis testing, clustering, and machine learning applications. They have worked with cloud platforms like Google Cloud Platform (GCP) and tools such as BigQuery, Looker Studio, IBM Cognos Analytics, RStudio, and Jupyter Notebook. With a strong background in bioinformatics and computational biology, they have conducted complex statistical analyses on high-throughput biological datasets, including microarray and CAGEseq data. Their work has involved regression modeling, network analysis, and functional annotation of genes to investigate patterns in neurodegenerative diseases and metabolic processes. Additionally, the candidate has experience in ETL pipeline management, data warehousing, and visualization, ensuring effective data-driven decision-making. They have led multiple research projects, collaborated with interdisciplinary teams, and provided analytical consulting to Ph.D. and MSc students. Their communication skills are demonstrated through frequent presentations, progress reporting, and clear data visualization using ggplot2. With a strong foundation in project management, teamwork, and analytical consulting, they have contributed to various research and business intelligence initiatives, offering valuable insights to stakeholders.
Responsibilities:
- Performed statistical modeling and data analysis using R, Python, SQL, and Bash.
- Conducted IoT data analysis, including time-series forecasting, correlation, clustering, and hypothesis testing.
- Designed and maintained ETL pipelines for data extraction, transformation, and loading in cloud environments.
- Managed and analyzed large-scale datasets using Google Cloud Platform (GCP), BigQuery, and Looker Studio.
- Developed interactive dashboards and reports to support data-driven decision-making.
- Conducted bioinformatics research, analyzing high-throughput biological data such as microarray and CAGEseq datasets.
- Applied regression models, network analysis, and functional annotation to identify patterns in genomic and clinical data.
- Performed data preprocessing, transformation, and statistical analysis for sales, healthcare, and research applications.
- Provided analytical consulting and support to Ph.D. and MSc students in data analysis and statistical methodologies.
- Led data-driven decision-making by identifying key performance indicators and optimizing resource allocation.
- Developed and maintained documentation for data processing workflows and analytical pipelines.
- Presented research findings and project outcomes in meetings, seminars, and conferences.
- Created clear visualizations using R packages such as ggplot2 to communicate complex analytical results.
- Ensured data integrity, validation, and quality control in research and business analytics projects.
- Collaborated with interdisciplinary teams, including biologists, engineers, and business professionals, to extract insights.
- Managed and optimized database queries to improve processing efficiency and analytical accuracy.
- Conducted text analysis to compare and extract key differences from structured and unstructured medical reports.
- Developed predictive models to improve sales forecasting, budget management, and production planning.
- Assisted in project management by analyzing data from multiple collaborators and completing analysis pipelines.