Resume

Aspiring Data Analyst

Passionate and results-driven Data Analyst, skilled in R, SQL, Tableau, and Microsoft Power BI. Recent graduate of the Data for Energy Skills Accelerator program with a strong background in Biological Science from University. Proven track record in transforming complex data into actionable insights, from optimizing sales strategies to contributing to ecological research in Uganda. Ready to apply diverse skills in data analysis, modeling, and visualization to drive business decisions and innovation.

Key Skills

Technical Skills: R (ggplot2, dplyr, tidyverse), SQL, Tableau, Microsoft Power BI, Microsoft Excel (Power Query, DAX, Pivot Tables, Advanced Formulas).

Data Skills: Data Analysis, Data Modelling (Statistical, Regression and Linear Modelling), Data Visualisation, Database Design, Data Cleansing, Machine Learning, Tabular Data Structuring, Dashboards and Reports.

Soft Skills: Presentation, Team-player, Adaptability, Attention to detail, Organisation Skills, Critical Thinking and Time Management.

Personal Projects

January 2024 - Present

Data Analyst Volunteer

Collaborated with university students to analyse and interpret their data, providing insightful findings to enhance decision-making processes.
Conducted comprehensive data cleaning and manipulation, ensuring the accuracy and reliability of their datasets.
Developed and implemented statistical models and machine learning algorithms to extract meaningful patterns and insights from complex datasets using R.
Utilized data visualization tools to communicate results effectively, aiding in the understanding of data trends and patterns.
Actively engaged in knowledge transfer by teaching students the fundamentals and logic behind various machine learning and statistical models.

October 2023 - December 2023

Data Analytics Intern, Avado’s Data for Energy Skills Accelerator

Utilised Microsoft Power BI for sales data analysis to provide data-driven recommendations, contributing to improvements in overall sales and reduction in stock wastage.
Integrated external data sources, including insights from COVID-19 impact, temperature, rainfall, and 2022 events, enriching the analysis and providing a comprehensive view of sales trends.
Successfully addressed quality issues in the dataset, ensuring data accuracy and reliability.
Implemented data-driven insights to optimise stocking strategies, contributing to enhanced business performance.
Led a team to develop an interactive report to visualise and communicate key findings effectively to stakeholders.
Presented analysis and recommendations to stakeholders, fostering collaborative decision-making and alignment with strategic objectives.

July 2023 - August 2023

Tropical Biology Association Student, Kibale Forest, Uganda

Collaborated with a fellow student to conceive and complete a successful research project on the assessment of strangler fig host preferences.
Analysed and compiled the research findings into a scientific paper, subsequently presented in a research seminar.
Completed the entire project, from inception to presentation, in an impressive ten days.
Led the collection of 80 samples, involving species identification, tree measurements, and habitat preference assessment while prioritising health and safety protocols in a dense jungle.
Utilised R for data manipulation, visualisation, and statistical analysis, revealing that 60% of strangler figs are most found in 3 host species in Kibale, thereby filling significant knowledge gaps.
Presented research outcomes to conservationists and students, providing valuable insights for decision-making on interventions and conservation efforts.

Personal & Professional Projects

January 2024 - Current

Predicting Football Results with Machine Learning

Conducted comprehensive exploratory data analysis to uncover significant trends, correlations, and potential predictors within the dataset.
Employed advanced subset selection techniques to identify optimal model configurations and key predictors for enhanced prediction accuracy.
Leveraged R's powerful supervised learning tools, including multinomial regression, Linear discriminant analysis, and random forest algorithms, to forecast match results, encompassing win, loss, or draw outcomes.
Implemented a rigorous data splitting strategy to partition the dataset into training and testing sets, employing exponential and simple moving averages to generate accurate forecasts of match performances.
Achieved a commendable predictive accuracy rate of 68% on the test dataset, surpassing the performance of baseline models.
Developed an insightful and interactive report using Microsoft Power BI, facilitating visual comparisons between various machine learning algorithms and time-series methods to evaluate their efficacy in predicting football match outcomes.

November 2023 - December 2023

Discovering India's Air Travel Trends

Applied SQL for meticulous data cleaning, encompassing tasks like standardization, data population, segregation, deduplication, and enhancing data quality.
Developed an interactive Tableau dashboard customized for identifying budget-friendly airline tickets, enabling data-driven decision-making in the field of flight bookings.

September 2023 - November 2023

Football Optimal Squad Selection

Successfully conducted comprehensive data analysis for player performance by gathering and scrutinizing relevant metrics such as appearances, goals, assists, and game ratings.
Employed Microsoft Excel for meticulous data storage and utilized SQL for data cleaning, manipulation, transformations, and table joins to create a well-structured dataset.
Created a Tableau story that served as an interactive and visually engaging presentation, offering a clear narrative on each player’s contributions.

September 2023 - November 2023

Global Impact of Covid-19

Utilized SQL to extract data from 2 related tables from COVID-19 databases using JOIN and VIEW
Transformed and filtered data by using aggregating and filtering function to refine the dataset and to improve reporting process.
Created a dashboard in Tableau that provides a comprehensive overview of COVID-19 statistics.

September 2023 - November 2023

Nashville Property Sales

Utilized SQL for detailed data cleansing, addressing tasks such as standardization, population, segregation, deduplication, and overall enhancement of data quality.
Created a customized Tableau dashboard that enables the identification of cost-effective properties, fostering data-driven decision-making in the field of property investments.

July 2023 - August 2023

Strangler Fig Host Preference Analysis

Leveraged R Studio for an in-depth analysis of the host preference of strangler figs in Kibale Forest, with a focus on conservation efforts.
Contributed valuable insights that can guide and inform future conservation studies in the region

January 2023 - May 2023

Gut Resilience in Mice Analysis

Utilized R Studio to conduct a comprehensive analysis of gut resilience in mouse models exposed to antibiotics.
Performed thorough data cleaning using dplyr and tidyverse to eliminate incomplete or inconsistent data, ensuring the reliability of statistical analysis.
Applied the Box-Cox transformation to achieve a normal distribution of data, enhancing the validity of statistical tests.
Utilized linear modelling techniques to quantify the impact of antibiotics on gut resilience in the mouse models.
Employed ggplot2 for data visualization, enabling the clear presentation of how each gut model responds to antibiotics.

Education

September 2019- November 2023

Bachelor's Degree in Ecology

I graduated with a Bachelor's Degree in Ecology from the University of Edinburgh, where I learned the fundamentals of R coding. My academic journey equipped me with a strong foundation in ecological principles, data analysis, and research methodologies. During my time at the university, I actively engaged in fieldwork projects, honing my observational and analytical skills in diverse ecosystems. Additionally, I took specialized courses that specifically focused on data analysis techniques, providing me with a comprehensive skill set for handling ecological datasets.

Resume

Aspiring Data Analyst

Key Skills

Personal Projects

January 2024 - Present

Data Analyst Volunteer

Collaborated with university students to analyse and interpret their data, providing insightful findings to enhance decision-making processes.

Conducted comprehensive data cleaning and manipulation, ensuring the accuracy and reliability of their datasets.

Developed and implemented statistical models and machine learning algorithms to extract meaningful patterns and insights from complex datasets using R.

Utilized data visualization tools to communicate results effectively, aiding in the understanding of data trends and patterns.

Actively engaged in knowledge transfer by teaching students the fundamentals and logic behind various machine learning and statistical models.

October 2023 - December 2023

Data Analytics Intern, Avado’s Data for Energy Skills Accelerator

Utilised Microsoft Power BI for sales data analysis to provide data-driven recommendations, contributing to improvements in overall sales and reduction in stock wastage.

Integrated external data sources, including insights from COVID-19 impact, temperature, rainfall, and 2022 events, enriching the analysis and providing a comprehensive view of sales trends.

Successfully addressed quality issues in the dataset, ensuring data accuracy and reliability.

Implemented data-driven insights to optimise stocking strategies, contributing to enhanced business performance.

Led a team to develop an interactive report to visualise and communicate key findings effectively to stakeholders.

Presented analysis and recommendations to stakeholders, fostering collaborative decision-making and alignment with strategic objectives.

July 2023 - August 2023

Tropical Biology Association Student, Kibale Forest, Uganda

Collaborated with a fellow student to conceive and complete a successful research project on the assessment of strangler fig host preferences.

Analysed and compiled the research findings into a scientific paper, subsequently presented in a research seminar.

Completed the entire project, from inception to presentation, in an impressive ten days.

Led the collection of 80 samples, involving species identification, tree measurements, and habitat preference assessment while prioritising health and safety protocols in a dense jungle.

Utilised R for data manipulation, visualisation, and statistical analysis, revealing that 60% of strangler figs are most found in 3 host species in Kibale, thereby filling significant knowledge gaps.

Presented research outcomes to conservationists and students, providing valuable insights for decision-making on interventions and conservation efforts.

Personal & Professional Projects

January 2024 - Current

Predicting Football Results with Machine Learning

Conducted comprehensive exploratory data analysis to uncover significant trends, correlations, and potential predictors within the dataset.

Employed advanced subset selection techniques to identify optimal model configurations and key predictors for enhanced prediction accuracy.

Leveraged R's powerful supervised learning tools, including multinomial regression, Linear discriminant analysis, and random forest algorithms, to forecast match results, encompassing win, loss, or draw outcomes.

Implemented a rigorous data splitting strategy to partition the dataset into training and testing sets, employing exponential and simple moving averages to generate accurate forecasts of match performances.

Achieved a commendable predictive accuracy rate of 68% on the test dataset, surpassing the performance of baseline models.

Developed an insightful and interactive report using Microsoft Power BI, facilitating visual comparisons between various machine learning algorithms and time-series methods to evaluate their efficacy in predicting football match outcomes.

November 2023 - December 2023

Discovering India's Air Travel Trends

Applied SQL for meticulous data cleaning, encompassing tasks like standardization, data population, segregation, deduplication, and enhancing data quality.

Developed an interactive Tableau dashboard customized for identifying budget-friendly airline tickets, enabling data-driven decision-making in the field of flight bookings.

September 2023 - November 2023

Football Optimal Squad Selection

Successfully conducted comprehensive data analysis for player performance by gathering and scrutinizing relevant metrics such as appearances, goals, assists, and game ratings.

Employed Microsoft Excel for meticulous data storage and utilized SQL for data cleaning, manipulation, transformations, and table joins to create a well-structured dataset.

Created a Tableau story that served as an interactive and visually engaging presentation, offering a clear narrative on each player’s contributions.

September 2023 - November 2023

Global Impact of Covid-19

Utilized SQL to extract data from 2 related tables from COVID-19 databases using JOIN and VIEW

Transformed and filtered data by using aggregating and filtering function to refine the dataset and to improve reporting process.

Created a dashboard in Tableau that provides a comprehensive overview of COVID-19 statistics.

September 2023 - November 2023

Nashville Property Sales

Utilized SQL for detailed data cleansing, addressing tasks such as standardization, population, segregation, deduplication, and overall enhancement of data quality.

Created a customized Tableau dashboard that enables the identification of cost-effective properties, fostering data-driven decision-making in the field of property investments.

July 2023 - August 2023

Strangler Fig Host Preference Analysis

Leveraged R Studio for an in-depth analysis of the host preference of strangler figs in Kibale Forest, with a focus on conservation efforts.

Contributed valuable insights that can guide and inform future conservation studies in the region

January 2023 - May 2023

Gut Resilience in Mice Analysis

Utilized R Studio to conduct a comprehensive analysis of gut resilience in mouse models exposed to antibiotics.

Performed thorough data cleaning using dplyr and tidyverse to eliminate incomplete or inconsistent data, ensuring the reliability of statistical analysis.

Applied the Box-Cox transformation to achieve a normal distribution of data, enhancing the validity of statistical tests.

Utilized linear modelling techniques to quantify the impact of antibiotics on gut resilience in the mouse models.

Employed ggplot2 for data visualization, enabling the clear presentation of how each gut model responds to antibiotics.

Education

September 2019- November 2023

Bachelor's Degree in Ecology