Ngondzana Tikum Michael

Ngondzana Tikum Michael Telephone:- /- Email:-Skype: michael.ng SUMMARY I am a dedicated Data Specialist with a robust background in data analysis, modeling, and visualization. My expertise includes proficiency in programming languages such as Python, R, and SQL, complemented by advanced skills in visualization tools like Tableau and Power BI. With a proven track record of interpreting complex datasets, I excel at identifying trends and generating actionable insights that drive strategic decisionmaking. My strong communication skills enable me to present clear and engaging findings to non-technical stakeholders effectively. As a graduate in Big Data and an accomplished analyst with successful projects across multiple departments, I thrive in innovative and fast-paced environments. I am motivated by continuous improvement and eager to contribute to impactful projects that challenge the status quo. I look forward to leveraging my skills to make a meaningful impact in a forward-thinking organization. EDUCATION Professional Certificate in Data Science| 2024 (Ongoing) Harvard University and EDX Master in Information Systems Management (Big data)|- National Advanced Higher Polytechnic School Douala Bachelor of Science in Statistics |- University of Bamenda PROFESSIONAL EXPERIENCE DATA ANALYST INTERN, NOVEMBER 2024 – PRESENT, CIMENCAM Create a BI report for real-time transportation cost management; Check the supplier data transmitted to the TAC server; Manage tests in JDE; Monitor interactions with Group support; Monitor the department's IT projects internally, with the parties involved; Create a BI report to identify anomalies between JDE, LIFE and Google Drive reports DATA SCIENTIST, FEBRUARY 2023 – OCTOBER 2023 ENEO CAMEROON SA. Definition of data storage solutions, collection and analysis of relevant data for the company Construction of algorithms to improve search and targeting results; Development of prediction models to anticipate changes in data and trends Creation of adapted monthly dashboards in Power BI, directly focused on KPIs Maintaining data integrity and security through the implementation of robust data validation protocols and frequent data audits, resulting in reliable and accurate information. DATA ENGINEER, SEPTEMBER 2022 – DECEMBER 2022 WOMEN IN BIG DATA Implementation of the ETL process from source files, ensuring data integrity and integration. Designed and created a PostgreSQL database for efficient data storage and retrieval. Industrialize and automate data cleaning according to the selected specifications. Loading data into the database and using Airflow for data orchestration in Spark. Industrialize and automate data cleaning according to specifications Developed linear regression models using ML lib in Spark for predictive analytics. Assessing model accuracy and forecasting profits based on trained models. DATA SCIENTIST INTERN, AUGUST 2022 - SEPTEMBER 2022 THE SPARKS FOUNDATION Supervised ML prediction (linear regression, decision tree). Unsupervised ML prediction (K-Means clustering) Retail Sales EDA with Tableau (KPI focus) Time series analysis of COVID-19 data (Python) DATA ANALYST VOLUNTEER, AUGUST 2022 CATCHAFIRE INC Help Amba Farmers Voice design a professional survey and train staff to execute and manage the survey. This project saved $4,828, allowing the organization to improve services to refugees INFORMATION MANAGEMENT OFFICER, NOVEMBER 2021 - JANUARY 2023 INTERSOS HELLAS HUMANITARIAN ORGANIZATION Ensure the programming and updating of data collection tools (XlsForm-Kobo format) Ensure the quality of data collection. Support NGOs in the production of reports (Multi-sectoral Assessment Post Intervention Monitoring / Post-Distribution Monitoring); Maintain the MSA and intervention monitoring matrix up to date; Maintain the MSA recommendations monitoring matrix with the technical groups and clusters Design and distribution of visibility tools: Maps, Dashboard, factsheet and infographics; Ensure the sharing of RRM results with the GT (Working Group) and clusters; Strengthen the MSA and Intervention teams in mobile data collection (KoboCollect); DATA CLERK, OCTOBER 2019 - NOVEMBER 2021 ELIZABETH GLASER PEDIATRIC AIDS FOUNDATION Support the design and planning of monitoring and evaluation activities in response to operational needs; Develop and regularly update monitoring-evaluation tools adapted to the activities of the organization; Ensure the collection and reporting of data in the field to enable monitoring and evaluation in as much real-time as possible; Ensure the processing, analysis and drafting of summaries of the data collected, including to feed the project's contractual reports and indicator tables Enter data into various tools and databases accurately and in a timely manner DATA CLERK, MAY 2017 - FEBRUARY 2019 ELIZABETH GLASER PEDIATRIC AIDS FOUNDATION CERTIFICATIONS Spatial Data Science: The New Frontier in Analytics, Esri, October 2024 Google Certified Data Analyst, August 2024 Reproducible Research Fundamentals; The World Bank, December 2023 SQL for Data Analysis; LinkedIn, December 2023 Data Integration & ETL with Talend; Udemy, Juillet 2023 Scientific Computing with Python; freeCodeCamp, February 2023 AWS Machine Learning Foundations; Udacity, November 2022 Understanding Data Topics; DataCamp, October 2022 MS Excel Complete Course; Intellipaat, Septembre 2022 Master in Microsoft Power BI Desktop and Service; Udemy, September 2022 Python for Data Visualization; LinkedIn, November 2021 Tableau Certification; Simplilearn, November 2021 Data Visualization in R with ggplot2; LinkedIn, May 2021 Fundamental Data Analysis and Visualization Tools in Python; Udemy, October 2020 Certificate in Monitoring and Evaluation; Global Health Center, July 2020 COMPETENCES Programming Languages Python, R, SQL Data Analysis Data cleaning and preparation Exploratory Data Analysis (EDA) Descriptive and inferential statistics Communication Skills Presentation of results and reporting Writing clear and concise reports Storytelling with data Visualization Tools Tableau, Power BI, Matplotlib, Seaborn, Ggplot Database Management SQL (queries, joins, aggregations) Relational databases (MySQL, PostgreSQL, MS Server) Nonrelational databases (MongoDB) Statistics and Modeling Statistical modeling Machine learning algorithms (supervised and unsupervised)