I can dive deep into datasets to extract meaningful insights. Starting by collecting and cleaning raw data, ensuring its accuracy and completeness. Then various analytical techniques, such as statistical analysis and machine learning algorithms, can be used to identify patterns, trends, and correlations within the data.

Afterwards I can interpret the findings and translate them into actionable insights or recommendations for decision-makers. This often involves creating visualizations or reports to communicate complex information in a clear and concise manner.

Additionally, collaboration with other team members, such as data engineers and business stakeholders, is performed to understand the context of the data and address specific business questions or challenges.

I employ continuous learning as I need to stay updated on the latest tools, techniques, and industry trends to enhance my analytical skills and deliver valuable insights.

Overall, my role as your data analyst is dynamic and multifaceted, requiring a combination of technical expertise, critical thinking, and effective communication skills to unlock the full potential of data and drive informed decision-making.

• Python
• Machine Learning
• Deep Learning
• Classification Modelling
• Regression Modelling
• Neural Networks
• Forecasting
• Clustering
• Reinforcement Learning
• Natural Language Processing (NLP)
• Exploratory Data Analysis (EDA)
• Data Warehousing
• Data Preprocessing
• Data Cleaning
• Data Visualisation
• Data Storytelling
• Machine Translation - [WIP]
• Computer Vision - [WIP]

• Tableau
• Microsoft Excel
• Google Colab
• Visual Studio Code
• PyCharm
• Jupyter Notebook
• Tensorflow
• Apache Spark
• Pandas
• Scikit-learn
• Matplotlib
• Azure Data Factory