•Team Management: Led a team of 2 analysts to streamline sales functions and finance reporting, enhancing operational scalability. Managing dashboard migration from Einstein Analytics to Tableau and pipeline migration from Oracle to Snowflake.• Data Strategy: Served as SME for core business metrics. Led revamp of executive company KPI performance dashboard. Transformed data organization into a single table, cutting down refresh time to 1 hour from 1 day. Merged 12 dashboards into one, incorporating dynamic filters and parameters for enhanced scalability. Resulted in faster dashboard performance, quicker refresh, and improved reporting scalability. • Database Management: Managed and optimize our data warehouse pipelines (Snowflake) to ensure optimal performance and scalability. Writing efficient and effective SQL and Python queries to answer business questions.• Data Analysis: Redesigned global sales strategy QBR, collaborating internationally for reporting comprehension. Leveraged Tableau for auto-populated metric slides, enhancing scalability. Analyzed complex data for trends, extracted insights, and provided data-driven recommendations in cross-functional collaboration.• Data Modeling and Transformation: Collaborated with sales strategy stakeholders to understand their analytical needs and translated requirements into well-structured data models using SQL. Create tests for SQL models to ensure data quality and manage our daily SQL runs.

• Optimized client billing, reducing cycle time by 50% and enhancing transparency with real-time client account status dashboards for executives.• Business Systems Admin: Tableau Server Admin. Included implementation, acquisition and deployment.• Managed Tableau administration, overseeing data pipelines, user permissions, and onboarding.• Centralized financial and sales data through Microsoft SQL Server, delivering CFO and CRO dashboards from an enterprise data warehouse.• Conducted Tableau training for 200+ users, ensuring effective platform utilization.• Hired and managed a team of BI analysts to meet the newly created analytics needs of the company.

•Machine Learning: Employed Python to extract insights through data scraping, encompassing variables like location, device type, and model, which deepened understanding of team operations.• Data management: Constructed efficient data pipelines using a combination of SQL and Python to ensure smooth data flow and processing.• Automation: Created bots using Python to automate communication and task distribution processes.• Contributed to the IT logistics team, devising effective data capturing strategies to enhance performance and processes.• Developed interactive dashboards on Unidash and Tableau, optimizing workflows and providing leaders with actionable insights.• Achieved a 55% increase in task throughput by identifying and removing obstacles, promoting effective team communication.• Pioneered the creation of a real-time reporting Facebook product for the Environmental Health and Safety team.• Leveraged Tableau and Google Forms as the reporting and communication platform, enabling swift tracking and response to health-related issues.

• Developed and delivered comprehensive Quarterly Business Review (QBR) reports using Tableau, providing stakeholders with actionable insights to monitor and assess the effectiveness of the Help Desk.• Designed and implemented interactive dashboards using in-house reporting tools, enabling real-time tracking and analysis of critical metrics for continuous service improvements.• Conducted in-depth data analysis to identify areas for optimizing operational efficiency, reducing costs, and improving ticket solution times, resulting in enhanced customer satisfaction and streamlined Help Desk operations.

• Developed, collected, analyzed survey data related to organizational leadership and employee performance for HR programs to enhance business effectiveness.• Utilized HR metrics and measures to help the organization understand and action on human capital trends and areas of risk, telling the story of the associate experience with HR data.• Scrape, combine and clean compensation and wage data from multiple sources (public and private databanks) for performance management solutions.

•Created a model to predict the winner of an E-sports game(Dota 2). The model was created from 5 web-scraped features and 25 feature engineered predictors such as win rate histories, team experience, and other metrics to produce a 6% return.•Web-scraped, cleaned and merged all relevant data into manageable data frames.•Performed EDA to check model assumptions, find anomalies and created visual representations of the data to spot trends•Used a Random Forest Classifier Algorithm with Gradient Descent to build the optimal model•Created a visualization tool to pull out probability coefficients to model team win rates throughout time

• Worked extensively with excel to improve efficiency using pivot tables, VBA macros to automate workflow processes.• Proactively collaborated with marketers, schedulers and traders with projects. • Created and updated internal pricing models and database for oil-based products and oil-based derivatives

• Developed and maintained models to store information key to health officials.• Extracted, sorted and cleaned raw data into meaningful information using Excel.• Collected recommendations from health officials to develop research plans and identify relevant data and data sources. • Designed and continuously enhanced data for statistical modeling and analysis based on the University’s standards.