Peter R.

I am an accomplished Data Analyst with a proven track record of transforming complex data into actionable insights. With a strong background in statistical analysis, data visualization, and data-driven decision-making, I bring over 2 years of hands-on experience to your project. My expertise extends to various industries, including finance, healthcare, e-commerce, and marketing. Skills: Data Analysis: Proficient in data cleaning, preprocessing, and analysis using tools such as Python, R, and SQL. I have experience working with large datasets and employing statistical techniques to extract meaningful information. Data Visualization: Skilled in creating interactive and informative visualizations using tools like Tableau, Power BI, Google Data Studio, Excel, and Matplotlib. I can effectively communicate complex data findings to non-technical stakeholders. Machine Learning: Familiar with machine learning algorithms and techniques for predictive modeling, classification, and clustering. I can implement models using libraries like sci-kit-learn and TensorFlow. Statistical Analysis: Adept at conducting hypothesis testing, A/B testing, regression analysis, and time series analysis. I use statistical software like SPSS and Excel to derive actionable insights. Data Cleaning: Experienced in data cleansing and preprocessing to ensure data accuracy and reliability. Proficient in identifying and handling missing data, outliers, and inconsistencies. Data Mining: Skilled in extracting valuable insights from unstructured data sources, such as social media, web scraping, and text analysis. Database Management: Competent in managing databases, writing complex SQL queries, and performing data extraction, transformation, and loading (ETL) tasks. Problem-Solving: Strong analytical and problem-solving abilities to address complex business challenges and provide data-driven solutions. Communication: Effective communicator with a knack for presenting data findings in a clear and understandable manner to both technical and non-technical audiences.