About Me
I'm Mojtaba (MJ) Ghasemi, a Senior Data Scientist with 8+ years of experience building and scaling data products at the intersection of analytics, machine learning, and generative AI. I currently lead end-to-end product analytics at IQVIA for AIM, a healthcare-intelligence platform processing behavioral signals across 6,000+ medical and pharma websites.
Before IQVIA, I was a Senior Data Scientist at Ethica CRO, where I architected AI/ML pipelines for clinical analytics under GCP, FDA, and Health Canada compliance, and shipped LLM-powered SOP automation. Earlier I built predictive analytics at the William Osler Health System and led ML research in biomechanics at Polytechnique Montréal, where I earned my Ph.D. in Biomedical Engineering.
I care most about turning ambiguous business questions into defensible KPIs, designing experiments that actually move roadmaps, and making complex data legible to executives. Outside work I teach data science at Montreal College of IT and write onMedium. Based in Canada, authorized to work in the U.S. under TN visa.
Skills & Expertise
Depth across the senior data-science, ML, and AI-engineering stack, from production pipelines to executive-level decision support
Languages
Machine Learning & GenAI
Data Engineering & Cloud
Product Analytics & Experimentation
Experience
My professional and academic journey
Data Scientist
IQVIA · Canada
- Own end-to-end analytics for AIM, a large-scale intelligence platform processing behavioral signals across 6,000+ medical and pharma websites.
- Design and govern core product KPIs (audience coverage, engagement depth, signal quality) used to evaluate feature performance and prioritize roadmap.
- Build analytics pipelines (Python, SQL, Snowflake, AWS Athena) and executive-ready dashboards used by sales and account teams in multi-million-dollar renewals.
- Lead NLP and Generative-AI classification pipelines, improved signal accuracy by 20% and reduced manual curation effort by 40%.
- Partner with PMs and engineers to design A/B tests and quasi-experiments that directly inform product launches and deprecations.
- Act as analytical owner across cross-functional teams, translating ambiguous business questions into measurable hypotheses and defensible metrics.
Senior Data Scientist
Ethica CRO · Canada
- Architected and owned end-to-end AI/ML pipelines for clinical analytics under GCP, FDA, and Health Canada compliance, improved operational decision-making efficiency by 12%.
- Built and deployed LLM-powered SOP-generation workflows (AWS, Docker, GPT-based models), reducing documentation effort by 30% and standardizing clinical processes.
- Served as NRC IRAP project contributor, driving applied research that improved internal analytics workflows by 25%.
- Delivered real-time clinical dashboards (R Shiny, Python) used by sponsors and study teams across trials.
Data Science Instructor
Montreal College of IT · Canada
- Design and teach industry-aligned curriculum covering ML, analytics, and data engineering.
- Mentored 50+ professionals on applied projects, with 95% placement or career-advancement outcomes.
Data Scientist
William Osler Health System · Canada
- Built predictive analytics and dashboards on claims and EHR data to identify care gaps, reduced patient wait times by 15% and improved provider efficiency by 25%.
- Translated complex healthcare data into actionable insights for clinical and operational stakeholders.
Research Associate
Polytechnique de Montréal · Canada
- Led a multidisciplinary team developing ML models for sports-performance optimization using PCA, clustering, and cross-validation.
- Developed a low-cost markerless motion-capture system with Microsoft Kinect, managing extensive biomechanical databases (EMG, kinematics, aerodynamics).
- Supervised graduate students in experimental design and biomedical data analysis.
Ph.D. in Biomedical Engineering
Polytechnique Montréal · Canada
- Dissertation: Performance Evaluation of Cyclist's Position Using Machine Learning and a Depth-Camera-Based Motion Capture System.
Certificate, Advanced Machine Learning
Springboard · USA
- Capstone-driven program covering advanced supervised/unsupervised learning, deep learning, and production ML workflows.