Duna
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Jos, Plateau, Nigeria
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Jobs
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- AData Engineering InstructorAlyticsJan 2025 - Current (1 year)
- KTechnical LeadKwotFeb 2024 - May 2024 (4 months)• Oversaw house-keeping tasks and collaborated with developers to fix bugs, ensuring product market fit. • Conducted daily and monthly data retrieval/extraction for user reports and views/streams. • Created insightful dashboards to drive decision-making processes.
- DTechnical LeadDataboard TechnologiesSep 2022 - Jan 2025 (2 years 5 months)• Designed Clocker's architecture for scalability and performance, ensuring efficient handling of user demands and data volumes. • Led development team, assigned tasks, and conducted code reviews for high code quality and stable releases. • Built backend using FastAPI for optimized API performance and improved response times. • Implemented CI/CD pipelines using GitHub Actions for efficient deployment and reliability.
- LData EngineerLicensewareMay 2022 - Nov 2023 (1 year 7 months)• Created data pipelines and processing apps to extract data from APIs and documents, storing results in databases • Developed reports from processed data, supporting fast decision-making in software asset management • Utilized regular expressions and MongoDB aggregations extensively for data extraction and analysis • Performed data modeling to optimize storage and retrieval of license-related information
- T
Mobile EngineerTechFusion, FlutterMay 2022 - Current (3 years 8 months)I played a pivotal role in developing the successful Fuse-Go app for TechFusion, which is now available on both Play and App Stores. By implementing efficient development processes, we were able to increase app downloads to over 10,000 on the Play Store. - CLead Mobile Engineer - Founding PartnerChawboxMay 2022 - Nov 2022 (7 months)• Led the mobile team in building the Chawbox mobile app from scratch using Flutter, ensuring responsive and intuitive frontend design. • Translated Figma designs into code with Flutter and implemented GetX for efficient state management. • Successfully managed the project remotely, showcasing strong leadership and communication skills.
- DData AnalystDover Engineering LimitedApr 2021 - May 2022 (1 year 2 months)• Unified multiple dashboards using Django, Pandas, and SQL to streamline operational decision-making. • Developed ETL pipelines and Python scripts for data automation, enhancing data management and team productivity. • Automated reporting with PowerBI, Excel, reducing manual reporting time and improving efficiency.
- MMobile EngineerMarkaccy Intergrated Services LTDFeb 2021Joined a team of developers to speed up development. Launched an MVP less than a month after I joined.
- DMobile Engineer and InstructorDiscovery Hub LabondoMar 2019 - Apr 2021 (2 years 2 months)• Taught Java and Python as a Flutter Tutor and mentor at the Hub. • Developed an event ticket verification App for TEDxYola using QR code technology. • Utilized Python to send custom messages to TEDxYola Participants for efficient communication.
- OProgram AssistantOxfam in NigeriaJun 2018 - Mar 2019 (10 months)• Created trip and field reports for Oxfam in Nigeria, supporting the State Project coordinator. • Developed presentation slides and maintained Excel templates to streamline project operations. • Assisted in coordinating project activities and ensuring timely delivery of reports and presentations.
Education
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- PGP, Artificial Intelligence and Machine LearningTexas McCombs School of BusinessJan 2019 - Jan 2020 (1 year 1 month)
- JBachelor's degree, Computer Science and StatisticsJoseph Sarwan Tarka University MakurdiJan 2012 - Jan 2017 (5 years 1 month)
Projects (professional or personal)
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- WWeather Data ETL Pipeline using Astronomer and AirflowAug 2024Developed a streamlined ETL pipeline using Astronomer for efficient management of Airflow deployments. The pipeline extracts the latest weather data from the OpenWeather API, transforms it using Python, and loads the processed data into a PostgreSQL database on Azure. This project showcases the simplicity and power of using Astronomer to automate data workflows and manage data pipelines effectively.
- SSentiment Analysis of U.S. Airlines Using Twitter DataMay 2020In this project, I performed sentiment analysis on Twitter data to classify and analyze customer feedback for major U.S. airlines. Using a dataset from Kaggle, I categorized tweets as positive, negative, or neutral and further classified the reasons behind negative sentiments (e.g., "late flight" or "rude service"). The project involved text pre-processing techniques like tokenization, lemmatization, and removal of special characters, followed by vectorization using CountVectorizer and TF-IDF methods. I then built and evaluated classification models to predict sentiment, demonstrating my skills in NLP, machine learning, and model evaluation.
- BBank Customer Churn Prediction Using Neural NetworksMar 2020 - Apr 2020 (2 months)This project involves building a neural network classifier to predict whether a bank customer will leave the bank within the next six months, based on an open-source dataset from Kaggle. The dataset contains 10,000 records with 14 features, including customer demographics, account information, and credit details. The project focuses on pre-processing the data by removing unique identifiers, normalizing features, and dividing the data into training and testing sets. Using Python and deep learning techniques, a neural network model is built, evaluated, and improved to achieve higher accuracy in predicting customer churn. This project highlights skills in data preparation, model building, and performance evaluation using confusion matrices and
- PPredictive Modeling for Customer Term Deposit SubscriptionsJan 2020 - Feb 2020 (2 months)In this project, I developed a predictive model using historical data to identify potential customers likely to subscribe to a term deposit, optimizing marketing efforts. Leveraging the UCI Bank Marketing dataset, I conducted univariate and multivariate analyses to explore relationships between variables and the target outcome. I cleaned and transformed the data, built and evaluated baseline models, and developed ensemble models using Python libraries like scikit-learn. The models were fine-tuned through hyperparameter optimization, significantly improving accuracy and marketing hit rates. This project showcased my skills in data analysis, ETL processes, and machine learning model development.
- TThera Bank Personal Loan Campaign - Machine Learning ModelDec 2019Objective: Built a classification model to predict the likelihood of liability customers converting into personal loan customers for Thera Bank (Use Case). Data: The dataset included demographic information and the bank's relationship details with 5,000 customers. Methods: Conducted exploratory data analysis (EDA), trained a logistic regression model, and evaluated its performance. Also provided recommendations for improving model accuracy by tuning parameters. Outcome: Identified key customer attributes that influence personal loan acceptance, which can help the bank's marketing team optimize future campaigns for better results.