Eli Kekombe

Data Scientist with over 7 years of experience building machine learning models, predictive analytics, and automated data pipelines within technology-driven environments. Skilled in Python (Pandas, Scikit-learn), SQL, Power BI, and Palantir Foundry, with a proven ability to engineer features, train and evaluate predictive models, and deploy data-driven solutions that translate into measurable business impact. Comfortable operating across the full data science lifecycle — from data engineering and feature engineering through model development, validation, and stakeholder communication — with a track record of improving operational efficiency and reducing costs through automation and predictive analytics.

Lead Data Scientist - Enterprise Technology Client (NDA) - Dallas

(2025-01 - 2026-01)

• Designed and implemented automated Python-based logging systems and predictive models, increasing operational response speed by 30% and saving $115,000 annually.
• Built and evaluated predictive analytics models using Python and Scikit-learn to forecast operational incidents, reducing incident response time by 30%.
• Developed and maintained Power BI dashboards for real-time operational reporting, providing executive leadership with actionable insights across multiple projects.
• Architected technical data schemas for end-users, reducing recurring support tickets by 40% and improving data consistency.
• Led a data modeling initiative to streamline ETL and feature-preparation processes feeding downstream models, resulting in a 25% reduction in manual data handling.
• Developed a real-time executive dashboard that improved visibility into operations and supported data-driven decision-making.
• Collaborated with cross-functional teams to enhance analytics and machine learning capabilities in support of emerging platform initiatives.
• Managed multiple analytics and reporting projects simultaneously, ensuring compliance with organizational standards.

Senior Data Engineer / Data Scientist - Alten - Dallas

(2024-01 - 2024-12)

• Designed and managed automated deployment pipelines in Palantir Foundry, reducing system downtime by 20% and improving rollout stability.
• Built data preparation and validation workflows in Python and SQL to support downstream analytics and modeling efforts, increasing deployment success rates to 95%.
• Developed SQL-driven Power BI dashboards to provide critical operational insights for global IT operations.
• Oversaw large-scale hardware and software rollouts, ensuring data consistency and compliance with organizational standards.
• Authored diagnostic manuals and troubleshooting guides that improved deployment success rates and reduced troubleshooting time by 35%.
• Supported operational reporting and analytics initiatives, delivering Power BI dashboards for executive and project-level visibility.
• Collaborated with cross-functional teams to support analytics and platform enhancements.

Data Scientist - Accenture - Dallas

(2023-06 - 2023-11)

• Delivered high-fidelity Power BI dashboards using SQL to provide executive leadership with visibility into global operations.
• Performed statistical analysis and root cause investigation on complex system issues, identifying patterns and supporting process improvements.
• Led data integrity and system monitoring projects, using automated Python scripts to improve reporting accuracy and reduce escalation rates by 20%.
• Automated data cleanup and validation processes, increasing reporting accuracy and reducing manual intervention by 30%.
• Built Power BI dashboards that improved executive reporting and decision-making for a global client.
• Supported multiple analytics projects simultaneously, balancing competing priorities in a fast-paced setting.

Data Support Specialist - Apple - Dallas

(2022-08 - 2023-06)

• Created resolution playbooks based on historical data trends and pattern analysis, decreasing Average Resolution Time (ART) by 25%.
• Developed a data-driven training program and mentored new hires on advanced troubleshooting techniques, improving first-call resolution rates by 15%.
• Analyzed support data to identify process improvement opportunities, streamlining workflows and reducing manual effort.
• Introduced process improvements that reduced ART by 25% and enhanced customer satisfaction.
• Collaborated with cross-functional teams to ensure data accuracy and compliance with organizational standards.

Data Support Associate - Amazon - Dallas

(2019-08 - 2022-05)

• Automated escalation workflows and ETL triggers using Python, reducing system downtime by 18% and optimizing resource allocation.
• Established standardized device configuration procedures, minimizing data entry errors and improving setup efficiency.
• Standardized configuration procedures, decreasing data entry errors and increasing setup speed.
• Supported deployment optimization projects, ensuring consistent data handling and compliance with company standards.
• Collaborated with IT and business teams to streamline technical support processes and improve operational efficiency.

Master of Science - Data Science - Grand Canyon University (2025-01)

Bachelor of Science - Computer Science - University of Texas at Dallas (UTD) (2022-01)