Linda Abudulai

Detail-focused Data Analyst, with over three years of experience in technology and project management as well as strong communication skills seeks a position where master’s level education, previous experience, and interest in data analytics can drive innovative decision making. Knowledgeable of the complete DSA Project Life Cycle, data warehousing, process validation and business needs analysis. Proven to understand customer requirements and translate into actionable project plans. Dedicated and hard-working with passion for Big Data and data science and analytics .

• Certifications Research Methods-West Africa Civil Society Institute Research Advocacy-West Africa Civil Society Institute Youth Advocacy Forum-British High Commission Interests Research and data gathering Data carpentry and Visualization Research Advocacy.

• Developed a Machine Learning classification model on the factors that affected the loss ratio of the alternate channel department.
• Worked with Customer Experience Department on a postcard project to pull data of customers without mail preferences or with paper preferences to convince them to switch to paperless formats.
• Analyzed Cerner Corporation's Diabetes data and developed a classification machine learning model on the factors that affect diabetes diagnoses.
• Developed a focused data story on Malaria using the stages of the project life cycle. The dataset was sourced from the World Health Organization.
• Findings in this data story telling projected WHO regions that is most affected by Malaria cases and deaths, top 30 countries severely hit by Malaria in the years 2016 and 2017, Relationship between number of deaths and cases reported, Malaria deaths and cases over the years using python programming language.
• Developed a data story using data sourced from a dating website.
• The findings projected the zodiac distribution of users which could serve as a population sample, cities with maximum usage, sex and age ratio, education levels of demographics, drinking habits, ethnic distributions and profiles using R statistical programming.
• Developed a data story using the Chicago Crime dataset and postgres sql language.
• Identifying entities and attributes, creating an ERD, creating tables(DDL), querying information_schema for table definition, loading data from giving dataset and developing distinct and useful queries to aid the police possibly.
• Findings after these queries projected total reports per each distinct crime in the Chicago area in the given year, sum of each distinct crime per police district per the given year, sum of crimes per block, average domestic arrests made per the given year and statistical groupings to find the average, variance and standard deviation of crimes to find statistics for various offences where arrests were made.