Zebrhan Measho

I am a results-driven professional with dual master’s degrees in Water Engineering and Data Science, bringing a unique blend of technical expertise and analytical insight to every project. My career spans both engineering and project management, where I have consistently delivered reliable solutions that meet client expectations and add measurable value.

In practice, I specialize in hydrological modelling, geospatial analysis, and predictive data science. Using Python, GIS, and advanced machine learning techniques, I transform complex climate and water resource data into actionable insights. This enables clients to make informed decisions, reduce risk, and optimize resource management. My ability to integrate engineering knowledge with modern data-driven approaches ensures that deliverables are not only technically accurate but also practical and impactful.

As a Scheme Project Manager at Balfour Beatty, I successfully coordinated multi-stakeholder engineering projects under demanding timelines. This experience honed my skills in structured communication, stakeholder alignment, and risk management—critical for ensuring projects are delivered on time, within scope, and to the highest standards. Clients can rely on me to manage complexity with clarity and precision.

What sets me apart is my commitment to quality, reliability, and long-term value. I approach each assignment with a focus on outcomes: clear deliverables, transparent communication, and solutions tailored to client needs. Whether it’s developing predictive models for extreme weather events, conducting geospatial analysis for infrastructure planning, or managing large-scale engineering projects, I bring a disciplined, client-focused mindset to ensure success.

In summary, I offer employers and clients a proven track record of delivering high-quality engineering and data analysis solutions, backed by strong project management experience. My goal is to help organizations achieve reliable results, reduce uncertainty, and unlock opportunities through the effective use of data and engineering expertise.