End-to-end analytical workflows and practical solutions.
Built a multi-stage skill standardization system in Excel with a controlled skill taxonomy and data integrity controls to enable normalized and dimensional skill demand analysis.
Developed an automated ETL pipeline that extracts highlighted skill mentions from annotated Word job postings using Python, then transforms and loads the data into a SQL Server star schema for multidimensional skill demand analysis.
Analyzed in-demand skill clusters across job postings using complex SQL queries and developed an interactive Power BI dashboard for exploring skill demand across skills, categories, and companies.
Self-directed based on independent job market research
Aug 2024 – now
I analyzed 35+ job postings to identify the most in-demand Data Analyst skill set, then designed and executed a learning plan based on that analysis. I completed online courses and hands-on coursework, then applied my skills in practical, real-world projects.
To support collaboration, track changes, and maintain clean, transparent codebases.
REPOSITORIES:
To clean and analyze large datasets, automate workflows, and build dynamic reports.
PROJECTS:
To query, filter, and combine large datasets, analyze trends, and turn raw data into high-impact findings.
PROJECTS:
To summarize data, test hypotheses, and analyze relationships for data-driven decisions.
PROJECT:
To clean and prepare data, run statistical analyses, and create scalable visualizations.
PROJECTS:
To model data, build interactive dashboards, and deliver actionable insights.
CERTIFICATE:
Microsoft PL-300: Power BI Data Analyst AssociatePROJECT:
Sep 2018 – Jul 2021
Honours CollegeApr 2019 – Jul 2021
Art History training has equipped me with several transferable skills that I apply in my data analysis projects:
My programming background has shaped my analytical thinking in several ways. Informed by error handling, I prioritize the early detection of data quality issues to produce accurate and reliable insights. I automate the analysis workflow wherever possible, focusing on reproducibility and long-term efficiency.
Programmatic problem-solving is a tool I use to develop a deep and thorough understanding of the underlying problem. I approach project execution iteratively, striving for correctness at every stage and treating incremental improvement as part of the process.
I take a cautious approach to interpreting results, considering the variables that may be influencing the outcomes. As with hypothesis testing, I take the results as evidence at a given level of confidence, rather than as proof.
I apply the same standard when communicating findings, designing visualizations that enable users to explore the data and extract usable insights, without requiring deep familiarity with the raw data. I am looking forward to observing how experts in high-stakes environments make decisions despite analytical uncertainty.
As a junior analyst, I understand my role as taking ownership of scoped analytical work with high standards of accuracy and reliability, contributing to the overall effectiveness of the team.
At this stage, I am comfortable working independently on foundational, end-to-end analytical tasks. The area where I expect to grow the most is domain knowledge, which is essential for working with more complex datasets and analytical challenges.