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Hi, I’m Peter Limo. I’m a data enthusiast and Epidemiology & Biostatistics graduate who loves turning numbers into meaningful insights. I work with Python, SQL, and R to clean data, build models, and create dashboards that drive public health decisions. I specialize in disease surveillance, geospatial analysis, and data visualization, and I enjoy collaborating with cross-functional teams to communicate complex findings to non-technical stakeholders. I’m motivated by solving real-world problems through data and AI, and I continually expand my skills across analytics, visualization, and data storytelling.…Hi, I’m Peter Limo. I’m a data enthusiast and Epidemiology & Biostatistics graduate who loves turning numbers into meaningful insights. I work with Python, SQL, and R to clean data, build models, and create dashboards that drive public health decisions. I specialize in disease surveillance, geospatial analysis, and data visualization, and I enjoy collaborating with cross-functional teams to communicate complex findings to non-technical stakeholders. I’m motivated by solving real-world problems through data and AI, and I continually expand my skills across analytics, visualization, and data storytelling.

Peter limo

Data Scientist, Data Analyst, Back-End Developer, +2

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Hi, I’m Peter Limo. I’m a data enthusiast and Epidemiology & Biostatistics graduate who loves turning numbers into meaningful insights. I work with Python, SQL, and R to clean data, build models, and create dashboards that drive public health decisions. I specialize in disease surveillance, geospatial analysis, and data visualization, and I enjoy collaborating with cross-functional teams to communicate complex findings to non-technical stakeholders. I’m motivated by solving real-world problems through data and AI, and I continually expand my skills across analytics, visualization, and data storytelling.…Hi, I’m Peter Limo. I’m a data enthusiast and Epidemiology & Biostatistics graduate who loves turning numbers into meaningful insights. I work with Python, SQL, and R to clean data, build models, and create dashboards that drive public health decisions. I specialize in disease surveillance, geospatial analysis, and data visualization, and I enjoy collaborating with cross-functional teams to communicate complex findings to non-technical stakeholders. I’m motivated by solving real-world problems through data and AI, and I continually expand my skills across analytics, visualization, and data storytelling.

Available to hire

Hi, I’m Peter Limo. I’m a data enthusiast and Epidemiology & Biostatistics graduate who loves turning numbers into meaningful insights. I work with Python, SQL, and R to clean data, build models, and create dashboards that drive public health decisions.

I specialize in disease surveillance, geospatial analysis, and data visualization, and I enjoy collaborating with cross-functional teams to communicate complex findings to non-technical stakeholders. I’m motivated by solving real-world problems through data and AI, and I continually expand my skills across analytics, visualization, and data storytelling.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Swahili

Fluent

Work Experience

Epidemiology & Biostatistics Intern at Kisumu County Referral Hospital, Department of Disease Surveillance

June 1, 2023 - September 1, 2023

Analyzed epidemiological datasets using Python and R to identify disease trends; created interactive Power BI dashboards for real-time disease surveillance KPIs; performed geospatial mapping with QGIS to visualize hotspots; conducted regression and time-series analyses to inform disease control policies; collaborated with cross-functional teams to communicate findings to non-technical stakeholders.

Project Analyst at Demola Global (ITATU & Kenya Ministry of Industrialization)

January 1, 2022 - June 1, 2022

Contributed to the 'Unlocking Telephone Farming in Kenya' project; built Power BI and Plotly visualizations to present insights; cleaned and processed large datasets with Python to ensure data quality; documented data pipelines for reproducibility.