DYLANDC

Bio

EDUCATION Western University London, ON Honours Specialization in Computer Science, Minor in Economics 2021 o Dean’s Honours List, Western Scholarship of Excellence Grant PROFESSIONAL EXPERIENCE Bond Brand Loyalty Toronto, ON Data Analyst, Client Analytics August 2021 – Present o Responsible for finding insights and delivering recommendations to senior client stakeholders regarding overall program health and targeted campaigns that provide information used to align strategic business objectives with data-driven solutions o Design and implement specific and valuable analytics solutions based on ambiguous client business needs, resulting in increased share of wallet, customer engagement, and brand recognition o Develop, evaluate, and implement non-supervised machine learning techniques to produce distinct customer groups which are most likely to respond positively to different types of engagement-driving stimuli o Co-headed the development of a Consumer Insights Report utilizing value & behavioural segmentations, along with a key driver analysis used to unlock insights and provide recommendations to our client on how to increase program engagement o Develop and maintain Tableau dashboards and automated email reporting which are viewed by clients daily, resulting in increased transparency for our clients and additional time for internal teams to work on other projects o Development, testing, and maintenance of silver and gold tables which are queried daily and used to produce analytics projects producing hundreds of thousands of dollars in revenue o Creation and maintenance of data dictionaries and ER diagrams for databases of over 1,000 columns from bronze, silver, and gold layer tables PROJECTS & ADDITIONAL An Algorithmic Analysis of Popular Music o Built a web scraping algorithm to gather, separate, and regularize structured and unstructured data on over 50,000 unique songs by utilizing JSON API calls and custom data-cleaning functions o Employed embedded feature selection methods alongside clustering and regression algorithms to create industry-wide and genre-specific predictions to analyze industry trends o Employed data visualizations which allow artists to easily understand why industry trends should be considered when producing new projects o Created methods to analyze why specific artists had success with certain projects to find ways to guide artists toward future success given emerging industry and genre trends o Discussed the potential for future partnership with a mid-size Canadian music label Analysis of NBA Players’ Marginal Revenue Product Versus Salary (Python) o Scraped and merged data to create a comprehensive basketball statistics database for the 2019-2020 season o Created linear, logarithmic, and decision tree models to find lesser-known player statistics with the highest impact on their salary and analyzed this information in combination with data on team market size and winning percentage to generate insights on player contributions to franchise value o Discovered that although good defence has a greater impact on winning than good offence, increases in players’ offensive abilities have a greater positive impact on salary than increases in defensive ability, implying that rostering superstars generates more revenue than improving a team’s winning percentage Technical Skills: Regression, classification, data cleaning, manipulation, and visualization, model selection, feature selection and regularization, clustering, behavioural segmentation, churn modelling, data storytelling, A/B testing Programming: Python (Scikit-learn, Pandas, NumPy, MLFlow, Plotly, SciPy, Seaborn, BeautifulSoup, Matplotlib, PyTorch), Spark, SQL, Databricks, Tableau, Snowflake, PowerBI, Java, Unix Interests: Cooking & Mixology (Host private events with curated menus), Brazilian Jiu-Jitsu, guitar (primarily blues, 9 years of experience), chess (ranked 1200+ on chess.com)