// Resumé
Kobby Sintim-Arthur.
Software developer and data scientist working at the intersection of energy and tech.
I started my career at Schlumberger (SLB), where I saw firsthand how much the energy industry relies on clean, accurate data. The analytical work was rewarding, but I kept gravitating toward how the systems processing that data were actually built, which pushed me to teach myself software development and spend the last few years building data-driven web applications from the ground up. I recently completed an MSc in Petroleum Engineering, where I brought those skills into my thesis: a deep learning model that automates complex image segmentation for geological data. My strongest fit combines an engineering background with data science and software skills, building systems that turn raw data into decisions.
Professional Experience
Software Developer (Contract)
Jan 2025 – PresentEdgebrcks · United Kingdom
- Co-developed a custom CRM platform and backend database, improving secure client data storage and daily workflows for the brokerage.
- Built RESTful APIs and relational databases for the custom CRM, allowing business users to easily query and extract clean data.
- Maintained the codebase through regular debugging, performance monitoring, and writing efficient Python scripts to ensure continuous data integrity for client operations.
Independent Software Developer
2023 – PresentSelf-Employed · United Kingdom
- Partnered with commercial clients to deliver custom web applications and internal software refinements, independently managing the backend database architecture and logic.
- Designed, built and launched Invoica (invoica.io), a full-stack client management and invoicing SaaS application using Python and PostgreSQL.
- Applied object-oriented programming principles to write clean, maintainable code for both client interfaces and data routing.
Data Analyst
2021 – 2024Schlumberger [SLB] · Ghana, West Africa
- Managed and processed live streams of offshore drilling data, ensuring data integrity and quality assurance for onshore engineering teams.
- Maintained 100% data completeness across projects by running strict quality control (QC) and quickly resolving sensor anomalies.
- Translated high-volume technical drilling data into streamlined operational logs, facilitating data-driven decision-making for non-technical leadership and cross-functional teams.
Technical Proficiencies
// Data Science & Machine Learning
// Data Engineering & Databases
// Domain Expertise
Technical Projects
MSc Thesis: Automated Deep Learning Data Extraction
- Built and trained a deep learning model (U-Net architecture) using Python to automate complex image segmentation, taking the project from initial exploratory data analysis to a validated algorithmic model.
- Replaced manual data interpretation with a reliable machine learning solution, reducing overall processing time by 80% while maintaining strict statistical accuracy.
Equinor Volve Time-Series Analysis & Dashboard
- Conducted advanced time-series analysis on real-world energy datasets using Python (Pandas, NumPy) to extract insights on production trends and field performance.
- Developed a Python-based data pipeline to automatically identify and clean sensor anomalies, mirroring the data integrity workflows required for industrial reporting.
- Built and deployed an interactive Streamlit dashboard to visualize complex metrics, translating technical data into clear, actionable storytelling for non-technical audiences.
Education
Personal Interests
Acoustic and electric guitar, exploring emerging software frameworks, building independent side-projects, and experimenting with AI tools.
© 2026 Kobby S. Arthur. All rights reserved.