Jul 2022 – Feb 2023 · 7 mos · Mountain View, California, United States

• Eliminated 16 hours per quarter of reporting and increased visibility for SaaS go-to-market reporting by building reporting layer with BigQuery, SQL, and DBT and automating Tableau dashboard.
• Automated complex analytics reporting to a degree thought impossible by translating business requirements into data transformations and SQL logic and working with data engineering to ingest data into data warehouse.
• Analyzed and evaluated the effectiveness of 11 heuristic customer health metrics using account-level NRR, descriptive statistics, and data analysis techniques with Python and Jupyter Notebook.
• Increased accounts by 2,000+ for marketing and sales to contact by updating SQL and Python logic in Airflow and meeting tight deadline before industry conference.
• Saved 2 hours of onboarding time per new employee by creating DBT training video to share best practices with data scientists after receiving positive feedback from new hires.

Nov 2021 – Jun 2022 · 7 mos · Santa Clara, California, United States

• Decreased project timeline in fast-paced, enterprise, B2B company by building 383 visualizations in Tableau and saving 152 hours (46% of LOE) by data modeling, thinking strategically, and stakeholder management.
• Through teamwork and tenacity, improved usability of customer success dashboards using 35M rows and 14.9GB of data by revising data modeling, tuning performance, and collaborating with business stakeholders.
• Improved scalability and maintainability of BigQuery SQL code in Tableau dashboards by eliminating two-thirds of code from 12 data visualizations by using problem solving and conditional statements.
• Shared best practices and collaborated with business partners, data analysts, and data scientists to spread Tableau and SQL knowledge during data infrastructure migration project.
• Improved performance and usability of BigQuery SQL-based Tableau dashboards by combining queries (reducing by 50% in some cases); converting into aggregate, window, and LOD functions; and rewriting for extract use.

Jun 2021 – Jun 2021 · 0 mo

• Scraped 23K rows of data, stored in NoSQL and SQL databases, and transformed data using Python data pipelines.
• Conducted exploratory data analysis and hosted Matplotlib data visualizations online.
• Determined no statistical significance between win rates of high and low penalty games after performing hypothesis testing and estimating the number of times teams were short-handed using penalty kill percentage.
• Communicated statistical analysis results using written communication, data visualizations, and presentation.

Oct 2018 – May 2021 · 2 yrs 7 mos · Oakland, CA

• Expanded self-service analytics tools by migrating existing reporting to BI stack by collecting requirements and metrics from internal stakeholders, expanding ETL pipeline to data warehouse, and building dashboards.
• Eliminated hours of reporting by automating repetitive reports by adding data sets to data warehouse, migrating quantitative and performance reports to R or SQL scripts, and writing documentation.
• Increased compliance to 75% for Mississippi state agency by designing and deploying Qlik Sense app that integrated data modeling, quantitative analysis, performance metrics, and data visualizations.
• Added 6,500+ lines of error-free SQL code to data warehouse ETL by designing a custom Excel workbook.
• Presented data collection, quantitative reporting, and data visualization improvement proposal to Mississippi state agency through verbal and written communication after analyzing existing systems and designing improvements.
• Improved decision making by expanding CRM system reporting by writing SQL scripts, expanding data sets and data models, and building quantitative and data visualization reports that incorporated performance metrics.
• Technical mentor to coworkers by collaborating on debugging, providing SQL assistance, and teaching weekly R sessions through presentations and technical writing.
• Removed manual updating of quantitative reports by building a data pipeline that scraped unstructured data, transformed the data set into a structured data model, and stored the results into an AWS RDS database.
• Removed two-thirds of quantitative analysis and statistical analysis reports in CRM system by using dataset permissions to limit access.
• Designed and deployed scalable Power BI data visualization reports using row-level security to limit access to data.

May 2016 – Oct 2018 · 2 yrs 5 mos · Menlo Park, CA

• Delivered quantitative and statistical reports on time by leading cross-functional teams to input their data, advising staff on data issues and data cleanups, and presenting insights through written and verbal communication.
• Collaborated on agency-wide data infrastructure improvement project by working on cross-functional teams to design, build, and deploy an agency-wide Salesforce CRM system.
• Decreased quantitative reporting time from hours to seconds by writing SQL scripts and building custom reports.
• Delivered effective reports by collaborating with cross-functional teams to understand their quantitative analysis and data visualization needs and meeting their preferences.
• Decreased reporting time by simplifying quantitative reports in analytics platform by reworking Salesforce CRM reports.
• Had agency-wide impact by delivering and presenting through written and verbal communication skills insights from quantitative and statistical reports to Development, Programs, and Executive Team.
• Decreased ad-hoc reporting time by hours by developing and improving custom quantitative reports that reported performance measures and metrics from previous requests.

Jan 2015 – May 2016 · 1 yr 4 mos · Santa Clara, CA

• Eliminated 6-8 hours of reporting time per quarter by building and owning interactive dashboard in macro-enabled Excel workbook that reported product performance and metrics.
• Collaborated with cross-functional teams from Marketing, Engineering, Operations, Sales, and Finance to acquire data, generate quantitative reports, and solve data challenges.
• Improved collaboration and cooperation between departments by creatively resolving conflicts of interest, adapting to different communication styles, and understanding different departmental points-of-view.