Mechanics' Institute is a historic, 501c3 non-profit membership library, cultural event center and chess program located in the heart of downtown San Francisco and serving the greater Bay Area. Established in 1854, the organization is a vibrant cultural hub offering a beautiful library setting, author talks, writing classes, book clubs, chess programs and education, and discussions by experts on a wide variety of current event topics. The Institute also houses a variety of other organizations and businesses that help to round out our offerings to the community at large.

I lead the Data Science function within the Global Technology org at Warner Music Group (WMG). We are focused on predictive modeling, ML, and AI applications, with some example projects around clustering similar artists, developing fuzzy-matching scoring engines to enable royalty matching, forecasting streaming demand across the world, and identifying similar songs.We are hiring across multiple teams, so if you're interested in tackling interesting and challenging problems with a talented group of colleagues, please reach out!

Fuzzy was a pet telehealth startup with a mission to make veterinary care more accessible to pet parents. I led the Data organization, with a focus on Analytics and Data Engineering. Our team focused on the following areas:• Developed business reporting from the ground up and shared insights across the business, including Marketing and Growth, Product, and Digital Health (Veterinary) Operations• Built the foundational Data Platform and Warehouse, focusing on data quality and automation• Drove improvements in pricing and product features through A/B tests and quasi-experiments• Led the Weekly Business Reviews for the executive teamOur tech stack centered around: Snowflake, dbt, R, Python, Google Sheets, Tableau, Amplitude, and AWS

I led the Data Science team that enabled Shipt's explosive growth by focusing on six different areas:1. Machine Learning2. Operations Research3. Analytics4. Data Warehousing5. Data Science Platform 6. Data GovernanceTo support these areas, we grew from a team of 3 when I started in 2016 to approximately 50 in 2020. The team is ambidextrous between Python and R and we use Tableau as our BI platform.Some of our highlights include: • building machine learning models across varied uses cases (e.g., recommendations, estimated shopping time, search) • understanding a multi-sided marketplace with 4 sides (consumers, shoppers, retailers, and advertisers), leading to solutions around forecasting demand (consumers) and supply (shoppers) • sharing reporting and analytics across the entire business (e.g., marketing, product, retailers & CPGs) • automating build and deployment systems for DS (we utilize Docker, Jenkins, Airflow, and AWS) • building new Data Lakehouse capabilities (on top of Snowflake)

While I didn't start as an Executive at Shipt, I was one of the 4 key players in our Series B fundraising in March-May 2017 (along with our CEO, CFO, and CMO) and was promoted to the Executive Staff in August 2017. Immediately afterwards, I was an integral player during due diligence before we were acquired by Target in Dec 2017; Shipt is now a wholly owned, independent subsidiary of Target.Since then, examples of my scope include: • corporate strategy development • presenting regularly to our Board of Directors in areas beyond just Data Science & Data Engineering and presenting in areas such as Business Operations, Marketing, and Business Development • co-leading the Technology & Product organizations for an interim period from May 2019 thru Nov 2019 (co-led with the CEO)

I led the Data Engineering and Catalog Operations organizations (focused on the e-commerce catalog) from data acquisition, standardization, cleaning, remediation, and pipeline delivery to our services & applications. I was the founding member of the group and built out the capabilities from the ground up, culminating in a team of approximately 40 in 2020 (~22 in engineering and ~18 in operations).Some highlights:• We were pivotal in making Shipt's explosive growth possible, building the marketplace from just 2 retail partners in 2016 to over 100 retailer pipelines in 2020. The bulk of this growth was from late 2016 through mid-2018 as we went from a regional player in the Southeast to a national player in just under two years.• Our pipelines processed ~400 million inventory and pricing records per day to provide accurate, complete, and consistent views of product data to our users in a timely fashion• We developed sophisticated web crawlers to build competitive pricing intelligence• The teams encompassed backend microservice development (in Golang), ETL (in Python), some tooling (React + GraphQL), and administration (via our admin portal + SQL scripts) capabilities.

Director of the largest in-house team at Vinyl and part of the Operational and Strategic leadership groups. I managed approximately 25% of the in-house employees.Team Development and Management• Responsible for recruiting, training, managing, and mentoring all Data Scientists, Analysts, and Database Developers on the team• Led over 50 internal team-training sessions, covering topics such as genetic algorithms, dynamic SQL, and effective dashboard design techniques, in languages/environments such as R, T-SQL, Tableau, and ExcelAnalytics and Data Science• Developed custom optimization routines for Naïve Bayes and Tree-Augmented Naïve Bayes models, drawing on techniques such as tabu search, simulated annealing, and tunneling to discover optimal feature sets in large state-spaces• Investigated new ways to detect concept drift in predictive models, to better maintain model performance under potentially changing circumstances • Oversaw Analytics Product development, including ethnicity prediction for improved image-serving within ads, enrollment rate forecasting for proactive marketing adjustments, and anomaly detection for website and system monitoringBusiness Intelligence• Led the continued expansion of the Operational Data Store and Data Warehouse to improve data access, increase data integrity, and facilitate faster reporting and dashboard performance• Developed a custom R package and scalable ETL scripts to handle a wide variety of client disposition data, allowing the company to better close the feedback loop on marketing efforts

Earlier Positions: Marketing Analyst (Dec 2010 – Nov 2011) and Data Scientist (Dec 2011 – Jun 2012)• Developed lead quality scoring models for clients to improve enrollment rates, leading to increases of up to 280% in the average Revenue per Lead from clients• Revamped the Recommendation Engine using collaborative filtering techniques, leading to a lift of approximately 8% in Revenue per User• Introduced several predictive models using a wide variety of methods, including fraud detection models and dialer prioritization models to determine optimal call-center calling orders• Designed numerous dashboards and visualizations to communicate findings across all levels of the business and to provide data access for non-technical audiences• Worked with the Development Team to build a framework for model deployment, including custom model class definitions in XML and function development in PHP• Led the transition from MySQL for end-user databases to MS SQL Server, leading to both a better end-user experience and also a more performant production environment• Introduced Tableau as a BI tool across the company to further democratize data and improve data literacy across the organization

Cornerstone Research provides attorneys with analytical support in all phases of business litigation, M&A, and regulatory proceedings. I consulted on cases across a wide variety of industries, from subprime lending, options backdating, fiber optics, and mining. My typical responsibilities included conducting market research, building financial models (e.g., DCFs), econometric models using ARIMA methods, and drafted and created reports and presentations in conjunction with academic and industry experts.

East Bay Chess was a center for organized chess activity in the East Bay nearly every day of the year through tournaments, lectures, lessons, and exhibitions. I built and designed our website, managed the finances, and helped with day-to-day chess activities from teaching to running over 50 tournaments.

Collected and analyzed financial data from Morgan Markets to analyze the performance of various instruments used to hedge mortgage pipelines.