Sinmiloluwa Ayoola

- | a-Li nkedin Portfol io Website Abuja , Nigeria Data Analyst/ Business Analyst SI NMI LOLUW A AYOOLA Skills • • SQL (SQL Server, MySQL, PostgreSQL) Excel (VLookup, Index, Match, Conditional Formatting, Pivot Tables) • Python (Pandas, NumPy, SciPy, MatPlotLib, Seaborn) • • • 9 Data Scrapping (Apify) Descriptive statistics • Microsoft Power BI (Data cleaning, Data visualization, Data Analysis) • • • • • • Chat GPT Excellent written and verbal Communication Self-motivated Problem-solving Adaptability Scrum Work Experience AP R/ 2 0 2 4 – T IL L DA T E ● ● ● Ca rryout s ocial media data s craping initiatives using a dvanced tools to extra ct actionable i nsights, i dentifying trends a nd patterns (using Power BI, Python or Excel ) that optimize engagement, i ncluding optimal posting ti mes and the relationship between impressions , best performing content type a nd follower growth. Pres ent key insights and data-driven recommendations to stakeholders through Power BI, enabling informed decision-making for performance opti mization. Creating s trategies based on these insights gotten and analyzed from scraped data thereby a chieving a n overall percentage i ncrease in follower base i n the last 9 months of 112.63% on Li nkedIn page. Overs ee s ocial media a ccounts, create compelling content to boost online visibility, enhance audience engagement, and attract new clients. AP R/ 2 0 2 2 – F E B/ 2 0 2 3 ● ● ● ● ● ● Provi ded Technical a nd Administrative Support i n Data-Related Processes, Troubleshooting, And Optimization of Data Ma nagement Systems . DATA AN AL YST IN TERN , HAMOYE – REMOTE Appl ied a dvanced statistical techniques, machine learning a lgorithms, a nd data visualization to uncover va luable insights, achievi ng a 30% i ncrease in decision-making accuracy. Conducted data cleaning and preprocessing using the python programming language, ensuring high data quality a nd reliability. Acti vel y engaged in workshops a nd s eminars to stay a breast of adva nced technologies, s howcasing commitment to continuous l earning and professional development. MA R/ 2 0 2 0 – S EP T/ 2 0 2 0 ● OPERATION OFFICER, N O RREN BE RG E R PEN SION S – GARKI, FCT Uti l ized Advanced Features of the Fund Fusion App and Excel to Streamline Data Processing, contributing to Improved Efficienc y a nd Precision i n Fi nancial Reporting, Leading to 50% Reduction in Reconciliation Account. Veri fied Documents for The Creation of Personal Identification Numbers (Pins) For New Pension Accounts, Ensuring Accuracy a nd Compliance. Contri buted to Collective Registration and Generation of Unique Pins for New Pensioners, Employing Data Analysis Techniques t o Ensure Data Integrity. J UL / 2 0 2 2 – SE P T/ 2 0 2 2 ● DATA AN AL YST/ DIG I TAL MARKETE R , L UDAY – WUSE, FCT I T I NTERN, HIIT PL C – L AGOS Engi neered a user-friendly Student Database GUI a pplication, streamlining the management of student records and reducing data retrieval time by 40%. ● ● Des igned the a pplication to facilitate s eamless data entry, retrieval, and updates, opti mi zi ng us er experi ence a nd opera ti ona l proces s es . Levera ged Python Programming Language and its libraries to develop a robust application, showcasing proficiency i n data analysis a nd s oftware development. N OV / 2 0 1 9 – N O V/ 2 0 1 9 ● ● DATA ANALYS T I NTERN, TAKEN MIN D TECHN OL O G I ES – REMOTE Led comprehensive preprocessing a nd cl eansing of datasets using Python libraries (Pandas, Numpy, Ma tplotlib, Scikit, a nd Seaborn), resulting in a 25% i ncrease in data accuracy a nd efficiency i n subsequent a nalys es. Appl ied a dvanced data visualization techniques to communicate and present insights derived from datasets effectively. Projects SAL ES AN AL YSIS (EXCEL & POWER BI)– Personal Project ● ● ● ● February 2024 Conducted thorough data cleaning procedures to ensure data accuracy, including identifying and removing duplicate values, addressing blank entries, and standardizing inconsistent formats. Utilized Power BI to visualize findings and create DAX measurements, enhancing data interpretation. Analyzed sales data to identify trends, patterns, and opportunities for growth. Conducted market research to understand customer behavior and preferences. Key Findings and Achievements: ● ● ● ● Achieved a remarkable 157% growth in the number of sales from January to December. Identified the Mac laptop as the top revenue-generating product. Maintained an impressive profit margin of 57.6% through effective cost management strategies. Successfully identified AA batteries as the most ordered product, demonstrating a deep unders tanding of customer preferences. ● Determined San Francisco as the country with the highest sales, highlighting the ability to analyze geographical sales data. DIABET IC PREDICT IV E AN AL YSIS( PYT HON ) – Personal Project October 2023 ● ● ● ● Imported and explored diabetes dataset containing information on pregnancies, glucose levels, blood pressure, skin thickness, insulin, BMI, diabetes pedigree function, and age. Performed data cleaning tasks, including handling null values, replacing zero values with feature means, and standardizing features using StandardScaler. Split the dataset into training and testing sets with a ratio of 80:20. Trained a SVM classifier with a linear kernel to predict diabetic outcomes. Key Findings and Achievements: ● ● Achieved a model accuracy of 78% using Support Vector Machine (SVM) algorithm. Implemented a Decision Tree model with an accuracy of 67% for comparison. Education G R AD U ATED N OV/ 2 021 B S C. COMPU T ER S CI EN CE, LAN D MAR K U N I VER S I TY – OMU - AR AN , KW AR A Certifications NOV/2019 SEPT/2020 DATA ANALYTICS AND VISUALIZATION WEB DEVELOPMENT WITH PYTHON