Welcome to Rachel's Fun World

I'm a skilled Accounting & Operations Professional with a passion for data science. With a proven track record as a founding employee in two successful startup operations, I've fostered collaboration among global teams, resulting in increased productivity and positive business outcomes. Now, I'm leveraging my transferable skills and knowledge to transition into data science, focusing on machine learning and predictive analytics.

                           

• Programming Languages: Python, R, SQL
• Data Analysis Libraries: NumPy, Pandas, SciPy
• Visualization Tools: Tableau, Matplotlib, Plotly, Seaborn
• Statistical Analysis: Hypothesis Testing, A/B tests, Parametric and non-Parametric tests
• Machine Learning Frameworks: TensorFlow, Scikit-learn, XGBoost, PyTorch
• Big Data Technologies: AWS, Hadoop, Spark, Hive, Docker

OCT 2023

• Collaborated with a multidisciplinary team during the Women Who Code Hackathon for Social Good 2023, developing Crisis Connect for BC's natural disasters.
• Conducted in-depth data analysis on natural disaster trends and their impact, using sources like "Our World in Data" and "WorldRiskReport".
• Developed a platform that promotes real-time interaction, connecting affected individuals directly to emergency services and vital resources.
• Contributed to a solution that emphasizes community interactions, real-time updates, and direct resource connections for expedited post-crisis recovery.

AUG 2023

• Implemented data cleaning and preprocessing on an extensive dataset.
• Explored relationships and insights using Exploratory Data Analysis.
• Trained and evaluated models, including Logistic Regression, Decision Tree, Random Forest and XGBoost, for accurate loan default prediction.
• Gained valuable insights into risk management, lending behaviours, and financial decision-making.

JULY 2023

• Collaborated with a diverse team during a 24-hour Hackathon sponsored by BrainStation and Google. Leveraged cross-functional teamwork, combining expertise in data science, UX/UI, and software engineering.
• Conducted comprehensive market research to understand the current gaps and needs related to AI education and used the insights from the research as a foundation to build a user-centric solution.
• Implemented data analysis to refine the approach and validate the strategies.
• Developed an innovative solution to educate users about new AI-related product features by prioritizing user control and empowerment as part of the educational experience.

JULY 2023

• Implemented topic modeling and sentiment analysis for user reviews.
• Focused on feature engineering and natural language processing techniques.
• Employed classification models to gain insights into user behaviour.
• Improved conversion rate by understanding customer sentiments.

JULY 2023

• Employed ETL processes to prepare mosquito tracking data for analysis.
• Leveraged statistical knowledge to analyze West Nile Virus spread through extensive exploratory data analysis.
• Utilized visualizations in Python and conducted hypothesis and correlation testing (t-test, Chi-square test).
• Implemented regression predictive modeling to understand mosquito tracking data.

JUNE 2023

• Integrated in-depth data analysis, interactive Tableau visualizations, and proficient SQL querying for exploratory analysis to reveal trends and behaviours in Bixi bike usage.
• Crafted an insightful visualization dashboard with drill-down capabilities to accommodate data inquiries.
• Reported findings and insights effectively through professional documentation that merged data-driven insights with robust visualization techniques.

Feel free to reach out to me on LinkedIn.

“Data is the new oil. It’s valuable, but if unrefined it cannot really be used.” – Clive Humby