Hi! I'm Dan Friedman.

I'm a life-long learner with a drive to use data science and machine learning techniques to solve challenging problems. I'm a Data Scientist with 3+ years of experience and have done work for the Chan Zuckerberg Initiative, Tesla Motors, Boosted Boards and TargetX. I'm a graduate of Metis and the University of Michigan.

I am on the lookout for my next big data science role. I want to help a company solve one of the world's biggest problems. Ultimately, I want to feel a sense of accomplishment from hearing that customers love our product and/or service and it helps them live happier and healthier lives. Fields particularly interesting to me are food, sleep, meditation, advice/coaching, productivity, transportation, shipping/logistics and housing. I'm open to working in other fields too!

Want to talk data science, new opportunities or about one of the fields listed? Shoot me an email 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.