About

As a Data professional with over 5 years of experience, I have a proven track record of transforming complex data sets into valuable insights. My expertise lies in leveraging data analytics tools and techniques to drive informed decision-making and support business growth. I possess a strong technical background in data analysis, data visualization, and statistical modeling. I am proficient in using tools such as Python, SQL, Tableau, and Excel to extract and analyze data, and I have experience working with both structured and unstructured data sets. Throughout my career, I have collaborated with cross-functional teams to identify business opportunities and develop data-driven strategies. I am a detail-oriented professional who understands the importance of data accuracy and completeness. I thrive in fast-paced environments and am always willing to take on new challenges. If you're looking for a data analyst who can help you make sense of your data and drive business growth, please don't hesitate to reach out. I am always interested in new opportunities to apply my skills and expertise.

Skills

  • Python Programming Language
    10
  • Data Analysis
    10
  • Software development
    10
  • R
    10

Experience

Livingstone Mumelo

Work experience
  • Agronomic practices, when combined with fertilizer application, can lead to
  • significant improvements in crop yield. Fertilizer provides essential nutrients for plant
  • growth and development, such as nitrogen, phosphorus, and potassium. But fertilizer
  • alone cannot guarantee high yields. Agronomic practices such as crop rotation, tillage,
  • manure application, soil erosion conservation, weeding and pest management can also
  • have a significant contribution on crop yield.
  • Excessive fertilizer use can lead to environmental problems such as soil degradation,
  • water pollution, and greenhouse gas emissions. Therefore, the optimal approach is to
  • use fertilizers when and where required in combination with appropriate agronomic
  • practices.
  • To decide when this combination we developed a machine learning tool based on
  • agronomic survey data from Babati district in Tanzania. A base random forest model
  • was initially created made up of 19 variables which was further tuned to include 10
  • variables based on their importance. The 10 variables included in the final model are
  • Wilting Index (WI), Latitude, SlopeDEM, Altitude, Longitude, PlantingDate, Topographic
  • Index (TPI), Village, WealthClass, and ManureFrequency). The response in
  • our case was computed as the relative ratio yield (RRY) between yields with use of
  • fertilizer and without. Where the response ratio was less than one is an indication where
  • use of fertilizer did not improve yield and thus in such a scenario the model will
  • recommend use of the other agronomic practices excluding use of fertilizer.
  • This Interactive tool was predicting on whether farmer should use fertilizer practice or agronomic practice so that to improve on crop yield. This tool was developed with Django backend and Reactjs frontend.
  • I designed the database using postgreSQL , created endpoints on Django backend to be accessed by Frontend.

Livingstone Mumelo

Work experience
  • October, 2021 - October, 2022
  • Fulltime
  • DATA ANALYSIS
  • Collected and processed data from multiple sources include twitter webscrabing, Journals, google forms e.t.c.
  • Performed data analysis and statistical analysis using python for the results and report generation for waste management, MSME's and innovation ecosystem in Kenya.
  • Conducted desktop research using journal articles, newspaper sources, questionnaires, surveys, and interviews to gather data for Kisumu Ecommerce ecosystem, MSME's and innovation ecosystem in Kenya.This involved development of Natural language processing module to simplify and automate the process of data collection.
  • Supported in design of user research methods such as surveys, questionnaires, and online polls using google forms and other paper forms for data collection.
  • Supported in planning and implementation of experimentation protocols such as the design of randomized control trials and A/B testing to test different hypotheses.
  • Developed visualization and visual information products (infographics,
  • factsheets etc) using python to support programme planning, monitoring and decision
  • making and provide value-added dissemination.
  • Working with partner organization I supported in Scanning and mapping the innovation and technology ecosystem and stakeholders in Kenya for initiatives and services related to the
  • Accelerator Lab’s goals and objectives.
  • Supported in Scanning and mapping global innovation trends and frontier methodologies
  • that are relevant to the Accelerator Lab’s portfolio for further exploration.
  • Contributed to planning and implementation of Accelerator Lab’s innovation
  • activities requiring expertise in data management and data analysis across
  • UNDP projects and programmes.
  • Supported in development of Accelerator Lab knowledge products (blogs,
  • articles, newsletters, reports etc).
  • Supported to develop a framework to capture the learning from the experiments

Livingstone Mumelo

Work experience
  • Responsible for overseeing all aspects of data management for the trial. In this role, I played a critical role in ensuring the success of the trial and advancing our understanding of pneumonia treatment and prevention.
  • DEVELOPING DATA MANAGEMENT FRAMEWORK
  • One of my key responsibilities was developing and implementing data management plans that complied with regulatory requirements and industry standards. I worked closely with the trial team to ensure that the data management plan aligned with the study objectives, and I provided guidance and support to the data team throughout the trial.
  • TEAM MANAGEMENT
  • In addition to overseeing data collection and quality, I was responsible for managing the data team, providing leadership and support to ensure that they were performing their duties effectively. I also provided subject matter expertise and support to other members of the trial team as needed, contributing to data analysis and reporting to provide insights and recommendations based on the data.
  • DATA GOVERNANCE
  • I also played a critical role in data governance. I ensured that data was managed in compliance with regulatory requirements and guidelines, including FDA and ICH guidelines, and that data privacy and security were maintained throughout the trial. I also collaborated with the trial team to develop and implement data governance policies and procedures to ensure that data was managed effectively across the trial.
  • Overall, my experience as a Lead Data Manager for a pneumonia trial gave me a deep understanding of data management and governance in the context of clinical trials. I am proud to have contributed to the success of the trial and to have played a critical role in advancing our understanding of pneumonia treatment and prevention.

Livingstone Mumelo

Work experience
  • 1. Data management and analysis using R, including data cleaning and exploratory analysis.
  • 2. Software development, primarily based on R and Shiny web programming for analysis and
  • visualization of data and analytical outputs.
  • 3. Spatial data analysis as part of the GSL team, including contributions to the upload and maintenance
  • of spatial data on the ICRAF Landscape Portal.
  • 4. Capacity building of ICRAF staff in the use of R for spatial data management and analysis.
  • 5. Contribute to stakeholder engagement workshops as part of projects applying decision dashboards
  • for evidence-based decision making .
  • 6. Contribute to the development of documentation for decision dashboards, including user manuals.
  • 7. Contributes to the overall mission of the GSL through the development of reproducible analytical
  • workflows.
  • 8. Machine Learning Models development for soil predictions

Livingstone Mumelo

Work experience
  • IT Specialist and graphics at   ICRISAT
  • 1. Software development and database administration
  • 2. Design systems and assess the effectiveness of technology resources already in use or new systems
  • that are being implemented.
  • 3. Create and design print and digital materials
  • 4. Retouch and manipulate imagesUse graphic design software and work with a wide variety of
  • media
  • 5. Assemble final presentation material for printing as needed

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