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Profil
Bildung
• Completed hands-on projects in health data analytics, predictive modeling, and statistical analysis. • Applied statistical and machine learning methods to assess intervention effectiveness. • Gained expertise in causal inference techniques, including instrumental variable analysis and synthetic control methods. • Developed skills in Python, SQL, and machine learning frameworks for health data research.
• Focused on healthcare financing, hospital management, and health policy. • Analyzed healthcare interventions using statistical modeling and real-world data. • Analyzed the economic and policy implications of public health interventions on patient outcomes, employing SPSS for data analysis. • Studied the effectiveness of community-based health worker programs on patient outcomes using quasi-experimentalhods.
• Trained in data management, data cleaning, and data visualization. • Conducted research using statistical software (SPSS) to analyze data. • Proficient in collecting, organizing, and interpreting clinical and pharmaceutical data. • Experienced in data visualization and reporting using tools such as Microsoft Excel, Power BI, or Tableau. • Gained foundational knowledge in pharmacology, therapeutics, and patient care.
Erfahrungen
• Extracted, processed, and analyzed healthcare data from various sources, focusing on patient treatment responses and health interventions. • Used machine learning tools (Python, Pandas, Scikit-learn) to predict patient outcomes, like survival rates and treatment effectiveness, aiding healthcare decision-making. • Worked with SQL to pull accurate data for analysis and performed statistical analysis in Python, R, and SQL to identify trends and evaluate treatment impacts. • Conducted propensity score matching (PSM) and difference-in-differences (DiD) analysis to assess healthcare intervention outcomes. • Developed predictive models for patient survival rates and created basic visualizations and dashboards using Tableau and Power BI to present insights to stakeholders.
• Conducted pharmaceutical quality assurance by analyzing lab data and ensuring compliance with regulatory standards. • Utilized statistical analysis and SPC methods to ensure the quality of pharmaceutical products, supporting cost-effectiveealthcare delivery. • Collaborated with cross-functional teams to improve data-driven decision-making in manufacturing and distribution processes.
• Gained hands-on experience in statistical methodologies and clinical trial design, using tools like SPSS and Python for accurate data analysis. • Demonstrated strong analytical skills and a solution-oriented approach, collaborating effectively with teams and adapting to challenges. • Acquired a solid understanding of research workflows and advanced analytical methods, including multivariate analysis to evaluate program outcomes. • Evaluated the WHO School Mental Health Program by applying advanced statistical methods (DiD, PSM) to assess intervention effectiveness and measured teacher well-being and mental health outcomes. • Developed an AI-powered chatbot for school-based mental health interventions, showcasing expertise in digital health solutions.
