Alexander Pan Email & Phone Number

New York, NY, US

• Executed decisions related to data processes, management, visualizations, accuracy, automation, and more
• Optimized BigQuery to ensure efficient SQL querying over large sets of complex data in combination with Looker
• Created the Looker views and models necessary to run our BigQuery data infrastructure to work in tandem with theengineering team’s embedding process
• Processed data into actionable insights for Network Next thru Looker data visualizations
• Developed customer-facing dashboard visualizations to allow game studios to make informed business decisions
• Trained, validated, and built machine learning models to provide insights, like feature importance and implicitfeedback, to investigate gaming issues for game studios, such as reported matches in relation to network.

• Automated various company alerts using Airflow, Snowflake, Redshift, and Slack
• Optimized N-offer sequence revenue using analytical, regression, classification methods. Project required weekly testing and reconfiguration of offers to send to product team to test.
• Performed regression modeling for user selection recommendations
• Developed a BG-NBD probabilistic model for customer lifetime value that showed promising results on a small 100,000 test population with 90% accuracy
• Completed ad hoc requests for multiple dashboard, chart, and analysis work for departments and people

• Write machine learning notebooks and scripts in Python for exploration and deployment
• Write SQL and data models to perform analyses and other data manipulation tasks
• Project 1: Creating a visual and interactive analytic dashboard to allow my clients to gain insights to make business decisions.
• Project 2: Looking at a public corporation's customer purchase data. The company is well known in the clothing/fashion industry. The goal was to leverage purchases to inform future marketing decisions.
• Project 3: Using machine learning regressors and classifiers to solve multiple issues, like identifying features related to binary and multi classification problems and multivariable regression analysis.
• Project 4: Ad-Hoc classification problem for big networking clientMuch more feel free to contact me to learn more about specific projects.

Completed a project involving multiple iterations of data munging, feature generation, and machine learning for Komodo Technologies

Worked with client in developing a classification model using 10 years worth of NFL game datasets. Project is in the beginning stages. Assisted in writing solutions and grading assignments and exams for a Multivariate Statistics and a Data Science Course. The topics include, but not limited to, Principal Component Analysis, K-Means Clustering, Hierarchical.

Phoenix, AZ, US

Identified(top 4% among 3000+ prospective data scientists) for skills in statistics, mathematics, data analysis, and computer science to participate in a rigorous 8 week data science fellowship program. Throughout the program, I developed my project that uses Riot Games' API in order to analyze, aggregrate 5.4 GB of match data. I used the in-game features.

Berkeley, CA, US

• Majorana and KATRIN Experiments (Nuclear and Particle Physics Research)
• Distinguished noise in MAJORANA Low Mass Front End Electronics wrt to experimental parameters. Best performance occurs with a minimal drain to source voltage of 0 V
• Ran Monte Carlo simulations and calculated and analyzed multiple 10 gb datasets to produce probabilities due to various systematic effects to investigate non-adiabatic effects in the KATRIN spectrometer
• Determined that KATRIN needs to increase the magnetic field strength from 3 G to 15 G in order to achieve 100% transmission rates for sterile neutrino searches. Thesis link can be found here.

San Francisco, CA, US

-Taught and lectured General Lab Physics focused toward non-calculus classical mechanics, electricity and magnetism, thermodynamics, and optical physics-Responsible for grading lab reports and creating weekly physics quizzes

West Lafayette, IN, US

• Dark Matter Research (Particle Physics and Cosmology)
• Investigated academic inconsistencies between peculiar velocities of the Sun and Milky Way for dark matter particle annual modulation research
• Calculated yearly WIMP particle velocities and error for four different academic results. Used parametric regression analysis to find curve fittings. Results showed maximum at December 1st and minimum at June 2nd

West Lafayette, IN, US

• High Energy Astrophysics Research
• Ran control tests and soldered photomultiplier tubes for the Very Energetic Radiation Imaging Telescope Array System telescope. Constructed energy spectrums with (<1gb) datasets with error propagation and polynomial.
• Ran Monte Carlo simulations for photons and calculated the χ2 values using Bessel’s corrections

Los Alamos, NM, US

• Dark Energy Research (Cosmology)
• Studied the efficacy of different parameters in discriminating theoretical models of dark energy using current and simulated datasets of 10-20gb.
• The geometric parameters give the most accurate information about the nature of dark energy by two orders of magnitude less than physical parameters. Complete results can be found here: http://arxiv.org/abs/1012.1591

Master Of Science (M.S.), Physics

Bachelor Of Science, Applied Physics In Computer Science And Astrophysics