Did you come to this page because I applied for a position with your company? Here’s an overview, what I’ve built in the past 10 months.
Examples of my computational biologist background are available here, here, and here.
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Projects at JoVE
Before the pandemic and ensuing lockdown crashed our economy, I worked for the Journal of Visualized Experiments (JoVE), which publishes science education materials and scientific video articles. The company sells subscriptions to academic libraries and markets to individual scientists to recruit new authors and increase product usage.
Project Name: Sales revenue prediction dashboard
Business Goal: Identify underperforming customer accounts.
Collaborators: Senior Sales leadership team
Approach: Defined key metrics to characterize customers, gathered and integrated data from internal and external sources, trained (Ridge) regression model, deployed visual dashboard.
Tools: R [dplyr, ggplot2, mltools, glmnet], Excel, Google Data Studio
Results: Focused marketing and sales efforts on customers that underperform relative to their peers. Put (high potential) leads on the map that were previously not considered.
Project Name: Data mining for customer success outreach
Business Goal: Automate data mining and reduce the cost of 300 man-hours per week.
Collaborators: Customer success team
Approach: Built ETL pipeline
Tools: Luminati Proxy Manager, Python [numpy, requests, BeautifulSoup, re]
Result: Scraped course information of over 1 million courses at 960 universities and saved the cost of 300 man-hours per week.
Project Name: Personalized high-volume email outreach
Business Goal: Identify narrow segments (by scientific area) to increase click-through rates of email outreach.
Collaborators: Marketing and Editorial leadership, IT
Approach: Retrieved millions of scientific literature records via API, gathered and validated emails, deduplicated leads, and segmented target audience for highly specific content.
Tools: Python [BeautifulSoup, Entrez, numpy, re], SQL
Result: Tripled click-through rate of email campaigns
Project Name: Internal data management pipeline
Business Goal: Prevent the Marketing team from reaching out to customers that where contacted by the Editorial, Sales, or Customer Success Departments in that same week.
Collaborators: Sales, Editorial, and Customer Success teams
Approach: Built a data management pipeline that gathered, deduplicated, and matched lead data with existing customers, and checked for the most recent touchpoint.
Tools: SQL, Salesforce, Python
Result: Improved brand perception.
Project Name: Marketing via matched content
Business Goal: Increase product usage by cross-linking with relevant external content.
Collaborators: CEO, IT
Approach: Implemented data management strategy and connected 100,000+ third-party publication records with the company’s content via natural language processing.
Tools: Python [nltk, pandas, numpy, scipy], SQL
Results: Prototyped algorithm that matches the company’s content to external content with high confidence.
Project Name: Tidy video production
Business Goal: Standardize data management and house-keeping.
Collaborators: Video Production team
Approach: Automate folder setup via a user-friendly script and implement a file naming convention.
Result: All four product development teams (Science Education) use my script, which ensures standardized file names and folder structure.
Project Name: Automated advertising keyword generation
Business Goal: Drive product usage of highly specialized, scientific journal articles.
Collaborators: Marketing team
Approach: Implement third-party Natural Language Processing API (see detailed post) that facilitates automated keyword generation for advertisement campaigns.
Tools: Python, MonkeyLearn API
Result: Enabled the marketing team to generate highly specific PPC keywords without scientific subject-matter expertise.
Project Name: SEO strategy, implementation, and monitoring
Business Goal: Increase organic traffic
Collaborators: Marketing team, IT, CEO
Approach: Create SEO strategy (technical and content SEO), guide IT to improve technical SEO, and work with an external vendor to improve content SEO. Designed and implemented an interactive dashboard to monitor SEO improvements.
Tools: Google Analytics, Google Console, Google Data Studio, Ahrefs, Ubersuggest, Moz
Project Name: Web analytics dashboard
Business Goal: Prototype a dashboard to monitor web analytics, which integrates subscriber account information and product usage.
Collaborators: CEO, IT, Marketing
Approach: R shiny dashboard that pulls subscriber information from SQL database, displays product usage by customer, and product (per selection on the interface).
Tools: R [shiny, tidyverse, googleAuthR, googleAnalyticsR, shinydashboard]