Davis Mongare

Master of Science in Data Science and Engineering

January 2023 - May 2025

University of Maine, USA

Focus: Big Data Engineering and Analytics (GPA: 3.8/4.0)

Technical Projects & Applications:

• Highway Safety Data Pipeline – Built a Spark-based ETL pipeline to process 500K+ crash records, reducing data processing time by 35%
• Built interactive dashboards with Tableau and Power BI, presenting fisheries trends to stakeholders and driving data-informed policy decisions.
• Database Development – Designed and implemented relational databases for optimized data storage and retrieval.
• Spatial Data Engineering – Designed and queried spatial database systems for mapping high-crash locations using QGIS and Python.
• Teaching & Curriculum Support – Mentored students in Python, SQL, and GIS workflows, developing reproducible analytical pipelines for large datasets.
• Real-Time Object Detection – Created computer vision models for image and video-based object recognition.
• Predictive Equipment Analysis – Built machine learning models to anticipate mechanical failures, reducing downtime.
• Crash Analytics & Visualization – Developed Power BI dashboards displaying crash trends and safety metrics used by transportation stakeholders.

Bachelor of Science in Civil Engineering

September 2013 - December 2018

Kenyatta University, Nairobi, Kenya

Focus: Civil Engineering and Analytics

Technical Projects & Applications

• Nairobi Intelligent Traffic System Design – Developed a feasibility study and road design optimization for smart traffic management using AutoCAD Civil 3D and InfraWorks. Integrated data-driven traffic simulations and predictive analytics using machine learning models (ARIMA, LSTMs) to forecast congestion patterns and optimize urban mobility planning.
• Transportation Systems Analysis – Performed traffic volume studies, speed-flow analysis, and capacity assessments to support transportation planning and safety improvement recommendations.
• Road Design & Highway Engineering – Designed road networks and highway corridors, implementing geometric road alignment principles in AutoCAD Civil 3D while analyzing real-time traffic patterns using data science techniques. Applied deep learning-based image recognition models to assess road conditions, detect potholes, and prioritize maintenance.
• Bridge Structural Analysis – Conducted structural integrity assessments of bridges using Prokon and STAAD Pro, evaluating load-bearing capacity and material strength with AI-driven predictive analytics. Built machine learning regression models to predict structural deterioration trends and integrated IoT sensor data for real-time anomaly detection in bridge performance.
• Traffic Flow Analysis & Vehicle Trend Forecasting – Applied machine learning and data analytics to assess vehicle trends and optimize traffic congestion models. Created real-time traffic monitoring dashboards using Power BI and Tableau, integrating live traffic sensor feeds, GPS data, and predictive analytics to enhance intelligent transport systems.
• Smart Infrastructure Decision Support System – Developed a data-driven decision support system using Python, SQL, and Power BI, analyzing geospatial and transportation data to assist policymakers in optimizing urban planning and infrastructure investment strategies.
• Autonomous Road Safety Monitoring – Implemented computer vision models using OpenCV and YOLO to analyze traffic camera footage, detecting traffic violations, accident-prone zones, and pedestrian movement patterns. Developed a dashboard in Tableau to visualize real-time road safety metrics for better enforcement strategies.

Graduate Assistant (Data Scientist)

September 2023 - May 2025

Maine Sea Grant Office, University of Maine, USA

• Data Visualization & Reporting – Developed Power BI dashboards to visualize fisheries and transportation safety trends, supporting data-informed policy decisions for stakeholders.
• Exploratory Data Analysis – Conducted EDA using Python (Pandas, NumPy, Statsmodels) to uncover key insights across environmental and transportation datasets.
• Database Development & Management: Designed and implemented a Project Management Database to streamline research workflows, ensuring efficient data storage and retrieval using SQL and PostgreSQL.
• Machine Learning & Predictive Analytics: Developed predictive models for marine conservation trends using Scikit-Learn, TensorFlow, and XGBoost, enhancing forecasting capabilities.
• Data Cataloging & Metadata Tagging – Standardized and documented research datasets for 10+ use cases, enhancing discoverability and data transparency by 30%.
• Customer Segmentation Analysis: Applied clustering algorithms (K-Means, DBSCAN) to segment fisheries stakeholders based on behavioral and economic factors.

Graduate Teaching Assistant

January 2023 - September 2023

University of Maine, ME, US

• Instruction & Mentoring – Guided and mentored 30+ students in SQL and Python, focusing on database optimization and foundational machine learning concepts.
• GIS & Spatial Data Coursework – Developed and taught lessons on spatial data analysis, enabling students to efficiently process and analyze geospatial datasets.
• Data Analysis Workflows – Created reproducible analytical workflows in Jupyter, teaching students best practices for crash data analysis and statistical modeling.
• Technical Support & Evaluation – Assisted in grading assignments, supporting course delivery, and ensuring students mastered core data engineering and analysis techniques.

Assistant Civil Engineer and Data Analyst

January 2020 - December 2022

German Rail Engineering, Nairobi, Kenya

• Highway Design Support – Contributed to roadway and pavement design projects, ensuring compliance with AASHTO and local design standards.
• Analyzed data collected from field investigations to create detailed maps of land areas.
• Predictive Structural Integrity Models: Used Deep Learning (CNNs, Autoencoders) to assess bridge and road structures, predicting potential failures and recommending preventive measures.
• Vehicle Trends Forecasting: Analyzed transportation datasets using time series forecasting models (ARIMA, LSTMs) to support traffic system planning and intelligent transport design.
• GIS-Based Smart Infrastructure Design: Used Power BI and Tableau to create geospatial dashboards, helping stakeholders visualize urban development patterns and traffic trends.
• Stormwater Management Optimization: Applied Machine Learning and Data Analytics in evaluating Nairobi’s storm drainage feasibility, improving urban flood control systems.
• Prepared reports and correspondence concerning direction of projects.
• Automated Civil Engineering Data Pipelines – Developed Python scripts for ETL (Extract, Transform, Load) workflows, automating the processing of geospatial, hydrological, and construction data for faster analysis and reporting.
• IoT & Sensor Data Analysis for Infrastructure Monitoring – Integrated IoT-based real-time sensor data from roads and bridges, applying predictive analytics to detect anomalies in structural health monitoring systems and improve long-term maintenance planning.
• Smart Traffic Signal Optimization – Developed a data-driven traffic light control system using reinforcement learning algorithms to optimize signal timing, reducing congestion and improving traffic flow efficiency in urban road networks.