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Health Care Health Care
Data Transformation and Warehousing Data Transformation and Warehousing
About me
I am a recent graduate with a strong academic background in Data Science. I have experience in data engineering, programming languages such as Python, C, and C++, and machine learning frameworks including scikit-learn, NumPy, SciPy, PyTorch, and TensorFlow. I have experience in project planning, prioritization, and meeting deadlines. I am a collaborative team player with excellent analytical and critical thinking abilities.
Data Science Machine Learning Problem Solving Data Analysis
AzureData AnalysisData ScienceData VisualizationMachine LearningNatural Language Processing (NLP)Predictive ModelingProblem SolvingSQLTime Series Analysis
Feb, 2023
analytical engineer freelance
Health CareHealth Care
Data engineering solutions
Developed an automated system for a medical services firm to optimise medication distribution and identify stockouts. Resulting in a 20% increase in the restocking rate and significant time savings. Built an automated data pipeline to convert CSV data to SQL in Azure Data Factory and utilised Python programming to implement machine learning algorithms for data analysis and visualisation.
Key responsibilities Key responsibilities
  • Developing automated systems
  • Optimising medication distribution
  • Identifying stockouts
  • Building automated data pipelines
Key achievements Key achievements
  • 20% increase in restocking rate
  • Significant time savings
  • Converted CSV data to SQL
  • Implemented machine learning algorithms
Jul, 2020
Aug, 2021
data engineer
Data engineering solutions
Provided data-driven solutions to enable informed decision-making for clients. Designed and optimized data pipelines using Azure Data Factory, resulting in improved efficiency and data transaction processing. Collaborated with cross-functional teams to ensure seamless integration of data sources and maintain data integrity. Applied Machine Learning to enhance results.
Key responsibilities Key responsibilities
  • Implemented data-driven solutions
  • Designed and optimized data pipelines
  • Collaborated with cross-functional teams
  • Ensured integration of data sources
Key achievements Key achievements
  • Contributed to predictive modelling
  • Enhanced efficiency
  • Improved data transaction processing
  • Maintained data integrity