Open to opportunities

Gemmar west

@gemmarwest

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Junior Data Analyst with expertise in machine learning and data science.

Uganda

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What I'm looking for

I am looking for a role that fosters innovation and allows me to leverage my data science skills while contributing to impactful projects.

I am a passionate Junior Data Analyst with a strong foundation in software engineering and data science. My experience includes implementing robust financial models and leveraging advanced statistical techniques to enhance data accuracy and drive business decisions. I have a proven track record of utilizing machine learning algorithms to optimize processes and improve outcomes, such as increasing campaign conversion rates by 18% through customer segmentation models.

Throughout my career, I have developed a keen interest in geospatial analysis and time-series forecasting, which I applied to enhance spatial data processing capabilities for the National Census. My commitment to data governance and compliance has enabled me to architect frameworks that ensure data security and quality, reducing potential legal risks. I thrive in collaborative environments and am dedicated to continuous learning and professional growth.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

Uganda Bureau of Statistics

May 2024 - Present (1 year)

Leveraged geospatial analysis techniques using PostGIS and Python’s GeoPandas library to enhance spatial data processing for the National Census, enabling precise demographic and geographical insights. Implemented a robust anomaly detection system using Isolation Forest and DBSCAN clustering algorithms in Python to identify and rectify outliers in survey data, improving accuracy by 15%. Architecte

Python PostGIS Geopandas Isolation Forest DBSCAN Data Governance Anomaly Detection

Data Scientist

Margel Holdings

Feb 2020 - May 2024 (4 years 3 months)

Developed and optimized customer segmentation models using unsupervised learning techniques, specifically K-means clustering in Python, to target marketing efforts, increasing campaign conversion rates by 18%. Applied Neural Networks using TensorFlow to analyze and predict customer service interaction outcomes, resulting in a 20% improvement in customer satisfaction scores. Led the design and depl

Python Neural Networks TensorFlow Pandas NumPy Power BI Customer Segmentation Business Intelligence

Junior Data Analyst

Cabral-Now-Emisha Pay

Jul 2018 - Feb 2020 (1 year 7 months)

Implemented and maintained robust financial models using regression analysis and time-series forecasting in R to manage risk and predict future transaction volumes accurately. Developed a dynamic pricing model using logistic regression, boosting revenue by 10%, and enhanced payment processing platforms by integrating machine learning algorithms to detect and prevent fraudulent transactions, reduci