Teaching and mentoring high potential students advanced and competition mathematics.

Founding data scientist for Beacons.ai. Helped Beacons’ data science stack evolve from post-seed to post-series A round. Drove major decision making in creator economics and growth strategies.

A short stint to help Databricks to predict its future growth.

Veteran super host help guests and hosts in the customer support team.

Product Growth: During Hesen's time at Uber's Scheduled Rides and Premium team, Uber's Scheduled Rides and Premium product line growth has been noted on the Uber's 2019 Q3 results: "Rides premium products generated significant growth - Rides premium products, including Comfort and Black, continue to scale with 41% gross bookings growth globally and 53% growth in the U.S. year-over-year. The higher margin profile of Comfort and Black helped to produce record Rides Adjusted EBITDA." Headline making projects: Uber Comfort, Scheduled Trip On-Time Guarantee ($10 for your late trips), Uber Premium Preference (tell your driver you are too tired to chat), Favorite Driver, Loyalty Program's Upgrade to Premium featureCross Functional Empowerment: Hesen has lead multiple company-wide, high business impact projects on the data science front, including: - "One Customer" effort as Uber to improve Uber Rides and Eats cross-sell. - Project Squeak, aimed at improving data science best practices in Uber's entire rider data science org.

I built the in-house search service for Postmates from ground up.

Founding team member of Bing Native Ads. Delivered user retargeting, near real time document understanding, and semantic keyword extraction components within two months.Designed and implemented high-volume offline model build pipelines, processing petabyte-scale data. Implemented corresponding online system with sub-minisecond latency.Owned keyword generation for MSN entertainment verticals. Improved multiple KPIs within one month of onboard.

Drove Amazon Total Value project to balance advertisement and retail presence for maximized revenue.Owned end-to-end optimization development. Applied statistical machine learning in Hadoop.Machine Learning Committee Member. Mentored junior research scientists. Public speaking: Big Data Exploration with Amazon, Joint Statistical Meeting (2013, Montreal Canada); Side by Side of Cloud Computing, Seattle Tech Forum (2014, Seattle).

Developed supervised machine learning algorithms for high-throughput data analysis in proteomics study. Contributed to multiple collaboration projects.

Constructed a real time alert system for search, ads and mobile metrics.

Developed parallel data mining programs for clinical genomics association study. Result was published. Co-authored R package for Bioconductor. The package was downloaded ~1300 times in year 2015.