Abel Tariku

Data Scientist & Quantitative Analyst with a strong background in GIS, spatial data science, AI models, and automated data engineering. Experienced in building Python and SQL pipelines, auditing large-scale datasets, and developing quantitative risk models, from time-series forecasting to interactive Power BI and Tableau dashboards. Passionate about translating spatial patterns, GIS data, and AI model outputs into clear solutions for teams and partners alike.

• Microsoft Excel
• Power BI
• Python
• SQL
• Tableau

1. AI Evaluation & Data Expert

   Mercor Intelligence

   juin 2026 to Aujourd’hui

   Remote

   • AI Model Evaluation & Benchmarking: Provided domain expertise to critique, evaluate, and benchmark frontier AI model outputs for a top AI lab, ensuring high accuracy, contextual fidelity, and logical consistency. • Prompt Engineering & Edge-Case Testing: Designed multi-turn prompt scenarios and executed stress testing to isolate model failure points, hallucination patterns, and reasoning gaps. • Dataset Curation & Alignment: Applied structured evaluation rubrics and data governance standards to curate high-signal datasets for Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). • Error Analysis & Quality Assurance: Conducted qualitative error analysis and systematic quality assurance (QA/QC) across multi-step analytical workflows, supporting continuous model optimization and safety alignment.

2. AI Data Specialist

   Stellar AI

   sept. 2025 to déc. 2025

   Remote

   • Data Quality Assurance and Governance: Architected multi-stage Data Quality Assurance (DQA) pipelines to identify and eliminate label noise in large datasets, reducing data corruption by 25% and enhancing the integrity of datasets used for production model fine-tuning • Model Evaluation and Testing: Conducted quantitative performance evaluations on complex LLM outputs and prompt pipelines to measure model accuracy, response quality, and output reliability over time. • RLHF Optimization: Optimized Reward Model performance within the Reinforcement Learning from Human Feedback framework by curating and validating high-signal preference datasets, driving a 22% increase in the consistency and reliability of model decision outputs • Taxonomy and Schema Engineering: Engineered structured annotation taxonomies for high-volume unstructured datasets, improving model intent recognition accuracy by 18% through nuance detection and multi-layered logic mapping

3. AI Data Analyst

   Telus Digital

   mai 2025 to sept. 2025

   Remote

   • Statistical Auditing & EDA: Directed Data Quality Assurance workstreams for Large Language Model (LLM) fine-tuning, performing deep-dive statistical audits and exploratory data analysis across 100,000+ critical data points to identify and mitigate model hallucinations and logic gaps • Data Harmonization & Search Relevance: Conducted high-fidelity search relevance analysis that improved algorithm ranking performance by 12% and synthesized unstructured data into production-level RLHF taxonomies with accuracy. • Cross-Functional Collaboration: Partnered with cross-functional teams to resolve systemic pipeline inconsistencies, reducing silent errors in the data pipeline by 15% to ensure system reporting integrity.

4. Team Lead

   Cineplex Entertainment

   oct. 2021 to avr. 2025

   Toronto, ON

   • Team Leadership and Operations: Led cross-functional teams of 15+ personnel in a high-volume entertainment environment, maintaining a 95% service rating and driving a 12% reduction in operational waste through strategic resource allocation. • Onboarding and Training: Coordinated a comprehensive, multi-stage training program for 20+ new hires, reducing average onboarding time by 15% • Regulatory Compliance: Audited operational workflows to ensure 100% compliance with company policies, safety standards, and regional regulations.

1. University of Toronto

   Honours Bachelor of Science, Geospatial Data Science

   Toronto, ON

   2025

   Major: Geospatial Data Science; Minors: Environmental Science, Management Relevant Coursework: Spatial Data Science, Regression Analysis, Computational Probability & Statistics, Natural Language Processing, Machine Learning