• manage the set-up of the district electoral office• implement administrative processes to ensure effective completion of required tasks• maintain the flow of assigned tasks by monitoring work status and adjusting as necessary to ensure task completion• ensure that policies and procedures are followed• manage and distribute office supplies and equipment used by field staff• provide training to and guiding the work of office staff• monitor the processing of accounts, payroll, and personnel records using EBC-specific databases and software• create work schedules for office staff that meet legislated requirements, make the best use of staff time and minimize overtime• supervise the mobile teams in their voting and counting activities• perform quality assurance functions, reviewing and evaluating the work of staff• liaise with Elections BC headquarters to resolve issues• manage the closing-down of the district electoral office, including overseeing the packing and return of supplies

• Utilized Python programming to extract and clean 100,000+ entries from at least two different data sources, e.g. CSV files, SQL database within a period of 1 week• Wrote SQL scripts query databases and manipulate them for future analysis, reducing the data analysis workload by 20%• Transformed large datasets to insights through statistical analysis and data visualization using PowerBI and Python, highlighting at least 5+ new patterns per full process of analysis made• Developed and implemented machine learning models using Python, leveraging decision tree algorithms to make accurate predictions of future business trends and improving forecasting accuracy by 14% • Communicated effectively with stakeholders, translating complex technical concepts into easily understandable insights by meaningful conclusions from analysis and models in reports, accelerating their process of understanding by a minimum of 3 days

• Constructed a volatility model using Python for tracking Vega and predicted future volatility, omitting 15% of extreme values • Developed a system using Python to monitor Delta from stock price data to remind traders about the Delta neutral for hedging, saving approximately 20 minutes per sequence of trading time for traders in the company • Monitored the company’s market risk models using VaR capturing potential losses from events like private lending over a year at a 95% confidence level, avoiding 10% of the company’s market risk• Investigated the factors influencing changes in Black-Scholes Greek Letters and reflected the results in presentations with 3D visualization, enhancing the understanding from the company’s software developer by 30%

• Prepared data plans and wrote comprehensive customer reports, enhancing customer satisfaction by 15%.• Evaluated customer engagement for a real estate company by analyzing statistical samples, enabling the real estate company to refine its strategies.

• Conducted financial needs assessments for clients to help expand BMO’s clientele; increasing weekly revenue by $100,000• Analyzed investment trends in different target client groups using Excel, provided monthly analytical reports and utilized data analysis tools to generate more comprehensive reports resulting in increased client satisfaction by 40%• Engaged customers in conversation to understand and address their financial needs, offering proactive advice and appropriate products, increasing loyalty by 33% and increasing product sales by 26%

• Predicted future cumulative profits data with regression forecasting techniques like Random Forest using Excel and Python, provided 20+ suggestions to the management team and achieved increased financial performance of the branch by 15% • Generated weekly reports from income statements accompanied by Excel visualizations providing internal users with an overview of the company's financial performance; implemented these tools for more than 30% of department trainees • Analyzed more than 50 financial product aggregate statistical indicators using Logistic Regression to identify trends and explain the performance of various financial products• Extracted financial product data with SQL to conduct a deep analysis to highlight trends