Lead Data Scientist

• Nov 2021 - Present

• Led Data Infrastructure developments of QuiGig Inc including ETL and Predictive Modeling.• Informed and educated the Executive Committee (EC) on the transformational power of data science, and convinced the EC to establish a Data Scientist job ladder.• Assembled and Led the customer discovery team focused on understanding and optimizing customer roadmap through experimental design, customer survey, customer retention rate, and referral network analysis. • Utilized the customer discovery results to optimize Google Ads Campaigns through search term selections, Ad text and landing page contents led to a drop of CPA by 35% and growth of landing page traffic by 47%. • Designed customer cross product attribute to identify and suggest other existing products likely to be bought by the existing customers resulted in drop of 13% Marketing cost. Show less

Data Scientist

• Aug 2020 - Nov 2021

• Developed and maintained a real-time KPI monitoring dashboard in close collaboration with the operation and IT departments resulting in 4.2 days faster per delivery.• Created a real-time Digital Marketing opportunity prediction through data migration from Google Ad and Facebook Ad Databases led to the opening of 3 new company branches.

Data Science fellow

• Sep 2020 - Nov 2020

Research Data Scientist

• Oct 2019 - May 2020

• Worked with Amazon Cloud services (AWS) to harness Machine Learning algorithms as well as physics-based models to create forecasting and cost optimization machines, led to cloud running software with potential saving up to $1.2MM per oil rig per year. • Modeled the ellipsoid of uncertainty for 3D positioning of wellbores to avoid collisions in crowded medium, led to MVP anti-collision software product (Safety Critical Directional guidance for drillers, inspired by GPS). • Role eliminated as a result of workforce reduction measures due to COVID-19 and OPEC-driven oil price fallout in March 2020. Show less

Data Scientist Intern

• May 2019 - Aug 2019

• Researched and developed a multidimensional Time series forecasting model for Shale oil/gas wells based on Continuous Deep Learning models. Improved the forecasting accuracy by 30%, performance speed by 5 times, and led to one SPE publication on automation. • Researched and developed a multidimensional Time series forecasting model for Shale oil/gas wells based on Continuous Deep Learning models. Improved the forecasting accuracy by 30%, performance speed by 5 times, and led to one SPE publication on automation.

Researcher Ph.D. Student in Computational Statistical Physics

• Aug 2015 - Jul 2019

• Collaborated with team of senior physicists and mathematicians to develop stochastic graphical network models for Social Networks, and identify social clusters resulting in extension of NSF grants and two peer reviewed publications• Conducted a multidisciplinary research with a team of environmental scientists and integrated Machine Learning algorithms Gaussian Processing Regression (GPR) and ARIMA as a tool for Climate Time series prediction, improved streamflow prediction by 10%, and identified the Climate Anomaly in Guadalupe river, Texas. • Developed Text mining (NLP) classifier for online toxic comments via LSTM, tf-idf Multinomial Naive Bayes using the scikit-learn and keras libraries, improved recall by 30% with respect to the benchmark model. Show less

Research Assistant, Master of Computational Biophysics

• Aug 2014 - Aug 2015

Developed C++ based Molecular Dynamics Simulation Softwares such as Amber/VMD in order to study Protein Folding and connecting Protein Misfolding to the occurrences of Diseases Wrote Shell/Awk/Matlab and queue scripts for running computationally intensive simulations and Data Management across Super Computers and Clusters

Graduate Teaching Assistant, Master of Computational Biophysics

• Aug 2013 - Aug 2014

I taught undergraduate and Pre-Med students basic university physics including Mechanics and Electromagnetism. I delivered lectures to guide students to connect Algebra-Based physical laws to their observations at Physics Lab.

Data Scientist

• Nov 2018 - May 2019

• Introduced Unsupervised and Supervised classification methods to PVT fluid phase behavior simulator for data-driven screening of oil well candidates for Enhanced Oil Recovery technology, which is led to screening speed up by 4 times, and presence of alternative in the absence of fluid simulator. • Introduced Unsupervised and Supervised classification methods to PVT fluid phase behavior simulator for data-driven screening of oil well candidates for Enhanced Oil Recovery technology, which is led to screening speed up by 4 times, and presence of alternative in the absence of fluid simulator.