Hi! I'm Dan Friedman.

I'm a life-long learner with a drive to utilize data science to solve challenging problems that can greatly benefit society. I work at WeWork in New York. I have years of data science experience through both qualitiative and quantitative methods. I've also worked for the Chan Zuckerberg Initiative, Tesla Motors, Boosted Boards and TargetX. I'm a graduate of Metis and the University of Michigan.

I have a plethora of interests in field. Want to talk data science, new opportunities or something else? Email me at dan@dfrieds.com

Twitter | LinkedIn | Github

Experience

Data Science Consulting

2017 - present

  • Research for Chan Zuckerberg Initiative (CZI): inferred 30-40% of U.S. adults with criminal records, ~25M people, are eligible for criminal record expungement. Insights helped CZI lobby regulators for state and federal legislation of automatic record clearance solutions.
  • Gathered continual insights on anonymous criminal record dataset of ~60K records to relay to CZI to ensure continued funding of project.
  • Tesla Motors: created Python library for drive simulation hardware to programmatically control car’s 12V battery; tests used to validate various aspects of Model 3’s design.
  • Designed and taught curriculum for 11-week master’s business analytics course in Python at Santa Clara University for 30 students; received positive reviews from students.
  • Created Random Forest classifier predicting trial rate conversion for personal trainer app with ROC AUC score of 0.88; model assisted team to interact with leads more efficiently.
  • Discovered drop-offs in user onboarding flow for trainer signups on app; suggested recommendations that were adopted by developers to redesign flow.

TargetX - Data Scientist

September 2017 - October 2018

  • Designed and implemented lead scoring model using engagement in social network app that estimated student college enrollment likelihood; guided Director of Admissions on outreach.
  • Implemented XGBoost classifier that predicted admitted college students’ likelihood to enroll.
  • Analyzed trends in customer data and produced 30+ data visualizations using Python and Plotly that were featured in customer-facing product.
  • Identified bottlenecks in email deliverability product through SQL queries and development of internal Chartio dashboards; insights used by support for diagnosis and helped engineers identify bugs and reduce time to send.
  • Created metrics and visualizations to highlight product value for renewal sales decks; helped close multiple $15K+ annual contracts.

Boosted Boards - Engineering Intern

April 2016 - December 2016

  • Provided evidence for engineers to make hardware and software changes before production by identifying outliers and issues in riding telemetry.
  • Created KPIs for engineering teams evaluating product performance from test riders highlighting engineering efforts towards hardware launch goals.