Data Scientist

• Conducted in-depth data analysis on cryptocurrency market trends and patterns, utilizing advanced statistical models and machine learning techniques to identify insights and opportunities for optimization
• Collaborated with a team of experienced data scientists to develop and implement predictive models for cryptocurrency price forecasting, resulting in increased accuracy and informed decision-making
• Assisted in the development of data visualization dashboards using tools such as Tableau and Python libraries in Jupyter Notebooks, providing intuitive representations of complex cryptocurrency data for stakeholders and clients
• Contributed to the improvement of data collection processes and data quality assurance measures, ensuring reliable and accurate datasets for analysis and modeling purposes

– Evaluating email campaigns for ISBA outreach using myEMMA by comparing analytical measures (open rate, click rate, etc.) from weekly newsletters in order to grow the department
– Actively working with a team of students to compare findings and brainstorming ideas to better progress our projects
– Using analytical tools found in Excel to analyze department data
– Using MySQL and MySQL Workbench to create databases and import data from other databases
– Exploring the capabilities of Raspberry Pi in a work setting

– Developed and implemented a comprehensive database system using Microsoft Excel, Access, and Jet SQL for the CASA program, enabling program officials and judges to assess and evaluate program efficacy efficiently.
– Collaborated closely with a team of professionals to gather requirements, design the database structure, and ensure data integrity and accuracy throughout the project lifecycle.
– Utilized advanced Excel functions and formulas to clean, transform, and analyze large datasets, providing valuable insights to support evidence-based decision-making.
– Designed and created intuitive dashboards using Microsoft Excel, enabling program officials and judges to visualize key performance indicators and track progress towards program goals effectively.
– Conducted regular data quality checks, identified and resolved data inconsistencies and discrepancies, ensuring the reliability and integrity of the database, and providing reliable information for program assessment and reporting.