Linda Oranya

Designed and implemented a robust, automated MLOps pipeline using Airflow, MLflow, and Docker for continuous model retraining, reducing maintenance overhead by 40%. Optimized data ingestion and aggregation methods for high-resolution, large-scale datasets, improving pipeline efficiency by 50%.

Mentored aspiring data scientists and provided guidance on career paths. Shared expertise in data science concepts and tools.

Tutored students in data science, helping them understand complex topics. Provided support and instruction in data analysis and machine learning.

Created an ML service that improved customer retention rate to about 67%. Worked with the Marketing team to understand customers through their Lifetime value.

Performed data science tasks and analysis for the company. Contributed to data-driven decision making.

Built and deployed predictive models leveraging Python and SQL to enhance audience targeting, resulting in a 30% increase in marketing campaign conversion rates within six months. Optimized data pipelines using Airflow, Docker, and AWS, automating the processing and integration of large-scale transactional and interaction data.

Developed scalable predictive forecasting models for stock markets, leveraging robust ML methods capable of handling large-scale data with continuous automated retraining. Led a team of 3 and organized bi-weekly meeting with Agile stakeholders.

Developed and implemented machine learning solutions. Contributed to the engineering of ML models.

Mentored young women interested in data, fostering their growth and development. Encouraged participation and engagement in the data community.

Currently pursuing a Master of Science degree focusing on advanced mathematical and statistical concepts. This program enhances skills in data analysis, modeling, and quantitative research methods.

Completed a Bachelor of Science in Systems Engineering, gaining foundational knowledge in engineering principles and system design. The curriculum covered various aspects of complex system development and analysis.

Obtained a National Diploma in Computer Engineering, focusing on practical skills in computer hardware and software. This program provided a solid base in engineering fundamentals and technical applications.

Completed a professional course in Data Science/Data Engineering, acquiring specialized knowledge and practical skills in data analysis, machine learning, and data pipeline management. This certification enhanced expertise in modern data methodologies.