Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 0

As a passionate and self-motivated data scientist, I have accomplished several noteworthy achievements despite having no prior experience or a formal degree. Here are the specific details of my accomplishments:

iFood CRM Analysis:

Dataset: I took on the challenge of analyzing a massive dataset from iFood CRM, which encompassed extensive customer information, order histories, preferences, and related data.
Techniques: Through self-study and exploration, I applied a range of data analysis techniques to extract meaningful insights from the dataset. These techniques included data cleaning, exploratory data analysis (EDA), statistical analysis, and data visualization.
Insights: During my analysis, I unearthed valuable insights into customer behavior, purchase patterns, popular food choices, regional trends, and any other relevant findings that could benefit iFood's business strategies and decision-making processes.
"Safe City" Analysis:

Dataset: I tackled the analysis of a dataset associated with the "Safe City" project, which involved data collected from "Register of violations of the 'Safe City' project"

•Analyzed the "Safe City" project violation dataset( 73149 recordings) which included information such as car brand, model, violation date, crossroad name, violation protocol name, and violation amount.
•Conducted exploratory data analysis to identify patterns and trends in the data.
•Generated insights on the most common violations, car brands and models involved in violations, and the average violation amount. Find out that Toyota was most fined brand

Self-taught: With unwavering determination, I pursued knowledge and skills in data science through self-study, demonstrating my ability to learn independently and acquire expertise without formal education.
Tools and Technologies: I proficiently utilized programming languages like Python and R, as well as essential data analysis tools such as Pandas, NumPy, and SQL. This showcases my familiarity with industry-standard tools and my ability to apply them effectively in real-world scenarios.
Learning Resources: To expand my knowledge and hone my skills, I actively engaged in online courses, tutorials, books.
Such as Coursera, Introduction to Statistical Learning
A highly skilled and motivated Data Scientist with overall 2 months in telecommunication industry experience. Proficient in applying advanced statistical and machine learning techniques to extract insights and drive data-informed decision-making. Good programming skills in Python, with expertise in data wrangling, exploratory data analysis, and predictive modeling. Demonstrated ability to develop and implement innovative solutions to complex business problems using cutting-edge tools and technologies. Excellent communication and collaboration skills, with a proven track record of delivering actionable insights to stakeholders. Committed to staying abreast of the latest trends and advancements in the field of data science to continually enhance analytical capabilities and drive organizational success.