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Data Scientist with 3+ years in data analysis & machine learning
Data Scientist and Project Management professional with over two years of experience in data analysis, process optimization, and cross-functional coordination. Proficient in leveraging A/B testing, hypothesis testing, and exploratory data analysis to uncover actionable insights, driving improvements in operational and commercial metrics. Skilled in automating ETL pipelines using Python, SQL, and AWS, and creating impactful data visualizations with Tableau, Plotly, and Seaborn to support strategic decision-making. Experienced in field-based stakeholder engagement, root cause investigations, and process documentation, enhancing system adoption and operational efficiency. Holds a Bachelor of Science in Project Planning and Management, with certifications in Machine Learning (ALX Africa) and AWS Cloud Practitioner (E-Mobilis Technologies). Fluent in English with basic proficiency in Swahili, committed to delivering data-driven solutions and fostering collaboration to achieve organizational goals.
AWS re/Start
AWS Cloud Practitioner
September 1, 2024 – December 31, 2024
ALX Africa
Data Science and Machine Learning
January 1, 2023 – December 31, 2024
University of Eldoret
BSc · Project Planning and Management
January 1, 2013 – December 31, 2017
Elink Agencies Ltd
Administrative Data Scientist
May 1, 2025 – Present
Kikuyu, Kiambu County, Kenya
Phoenix Analytics (Internship)
Junior Data Scientist
September 1, 2024 – April 30, 2025
Nairobi, Nairobi, Kenya
ALX Africa
Junior Data Scientist
April 1, 2023 – August 31, 2024
India
Customer Attrition Prediction App
June 18, 2026 – Present
Developed a web-based app using A/B testing and hypothesis testing to predict customer churn, improving detection accuracy by 70%. Automated ETL pipelines with Python and AWS, reducing data processing time by 40%. Presented insights via interactive Streamlit dashboards, driving cross-functional strategic decisions.
View ProjectCredit Scoring Model for Loan Risk Assessment
June 18, 2026 – Present
Built a machine learning model to assess loan risk, leveraging Scikit-learn for predictive accuracy and SHAP for feature importance analysis. Conducted exploratory data analysis to identify key risk factors, improving model interpretability for stakeholders. Deployed model insights to support financial decision-making, enhancing loan approval processes.
View ProjectAnomaly Detection System
June 18, 2026 – Present
Designed an anomaly detection model to identify outliers in operational datasets, improving error detection by 65%. Utilized statistical techniques and visualization tools like Seaborn to uncover patterns and communicate findings to stakeholders. Optimized model performance through feature engineering, enhancing system reliability for process monitoring.
Named Entity Recognition for Customer Feedback
June 18, 2026 – Present
Developed an NER model to extract key entities from customer feedback data, improving categorization accuracy by 60%. Applied NLP techniques to streamline complaint analysis, enabling faster resolution processes. Created visualizations with Plotly to present entity insights, supporting cross-functional operational improvements.
View ProjectCultural Fit Analysis
The candidate's project diversity, including customer attrition, credit scoring, anomaly detection, and NLP for customer feedback, indicates a broad interest and adaptability to different problem domains. Their experience in both an internship and a full-time role, along with certifications, shows a commitment to continuous learning and professional development. The blend of technical and project management skills suggests a collaborative mindset, suitable for cross-functional teams.
Soft Skills & Operational Fit
The candidate demonstrates strong communication skills through project descriptions and experience, emphasizing stakeholder engagement and presenting insights. Their project management background suggests an ability to coordinate and deliver end-to-end solutions. The focus on process optimization and problem-solving aligns well with operational roles requiring data-driven decision-making.