Description

Nasser is a skilled applied data scientist with extensive experience in data analysis, predictive modeling, and visualization. His diverse expertise spans multiple industries, including sports analytics, education, and aerospace. Nasser is proficient in Python and its many libraries including pandas, numpy, scikit learn, matplotlib and plotly and has a strong background in applying machine learning techniques to solve complex problems, including time series forecasting, ranking models, NLP driven textual analysis, media mixed modelling and more. He has worked on various projects, from optimizing models and analyzing racing performance to creating AI-based sentiment analysis tools. Additionally, Nasser has a keen interest in education and enjoys developing engaging lesson plans and learning assessments for high school and university-level students. His unique blend of technical knowledge and teaching experience makes him a versatile professional capable of driving data-driven insights and fostering academic growth

Languages

English
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

Allez Health
Data Scientist
January 2025 - April 2026 (1 year and 3 months)
• • Owned the data workstream from raw sources to final deliverables, structuring complex datasets for analysis.
• • Extracted insights through statistical analysis and presented clear findings to technical and business stakeholders.
• • Produced executive-ready visualizations, documentation, and summaries under project deadlines.
Data Visualization Time Series Analysis and Forecasting Python KPIs and Metric Definition and Monitoring Business Intelligence (BI) Strategy
Alt Sports Data
Data Scientist
January 2024 - Today (2 years and 6 months)
• • Structured large, unorganized datasets into analysis-ready form to support insight generation and reporting.
• • Benchmarked analytical findings against existing methodologies to validate accuracy and business relevance.
• • Delivered concise reports and visualizations to decision-makers under tight timelines.
Pratt & Whitney Canada
Data Scientist Internship
September 2018 - August 2019 (11 months)
• • Analyzed high-volume operational data to identify issues and support engineering and operations decisions.
• • Built automated reporting tools and dashboards, improving efficiency and reducing manual effort.
• • Supported time-sensitive analytical requests in a fast-paced, deadline-driven environment.