Current role
Data Analyst
Currently working at Aarista / Altea Healthcare on analytics, reporting, dashboards, and data product work.
Data Analyst Portfolio
Data Analyst building machine learning, GenAI, and BI projects with Python and SQL.
Focused on supervised learning, causal inference, forecasting, Power BI, and natural-language AI, with code and notebooks organized on GitHub.
Focus Supervised learning, causal inference, forecasting, natural-language AI
Tools Python, SQL, Power BI, PySpark, Fabric, Databricks
Education
McGill University
Master of Management in Analytics with training in applied analytics, experimentation, modeling, and business-facing data work.
Portfolio Projects
Selected GitHub projects.
Spotlight project
Natural Language to SQL Query Generator
A GenAI project built around translating natural-language questions into SQL, making structured data more accessible through an LLM-driven interface.
natural-language interface
query generation
prompt-driven workflow
Problem
Reduce the friction between plain-language business questions and the SQL needed to query structured datasets.
Approach
Built a notebook-driven GenAI workflow that maps natural-language prompts to SQL generation logic within a focused application setting.
Outcome
Added a more concrete GenAI project to the portfolio with a direct link to a real analytics use case.
GenAI experimentation
GenAI Models
Notebook-based generative AI experiments focused on model behavior, applied workflows, and prompt-driven exploration.
GenAI
Prompting
Notebook Workflows
Repository
Causal inference
Causal Inference Model for Bank Client Subscription
Built a project focused on estimating the impact of marketing campaigns on bank client term-deposit subscriptions using causal inference techniques.
Causal Inference
Marketing Analytics
Python
Repository
Supervised learning
PyTorch Multi-task Learning for House Prices and Categories
Developed a multi-task deep learning project that predicts both house prices and house categories in a single supervised learning setup.
PyTorch
Regression
Classification
Repository
Capabilities
Machine learning, GenAI, BI, and data engineering.
Generative AI and agents
Applied work around LLM systems, tools, memory, orchestration, and modern GenAI workflows.
Supervised learning and NLP
Classification, regression, anomaly detection, NLP, SHAP-based explanation, and notebook-based ML workflows using practical datasets.
Causal inference and analysis
Causal modeling, bias analysis, and experimentation approaches that help separate signal from correlation.
Data engineering and BI
SQL, PySpark, Fabric, Databricks, ETL and ELT pipelines, embedded Power BI, and structured project design for usable outputs.
GitHub Project Archive
Public GitHub repositories.
Loading projects from GitHub...
How I Work
Clear problems, readable outputs, reproducible structure.
Problem first
I prefer projects with a clear question, measurable output, and a reason the result matters.
Simple communication
Models and dashboards are most useful when the choices, tradeoffs, and conclusions stay easy to follow.
Reproducible structure
I favor project setups that make it easier for someone else to review the work, rerun it, and build on it.
Get in Touch