Alex led the development of several projects to bring Direct Sales Mobile to the forefront of technological innovation within the direct selling industry, including:1. A patented time-series recommendation engine, that sends daily content recommendations for business owners to share with prospective new members within DSM’s mobile prospecting app. Recommendations are determined by an algorithm utilizing forward-feeding neural networks and deep learning applications to output the recommended content such that each prospect’s conversion probability is maximized after a predetermined time interval. This engine has been in production for thousands of end-users since January 2018 and has achieved a significant lift in conversion rate for users who engage with recommendations. Alex developed the entire ML pipeline, including daily data ingestion, model execution, and loading of recommendations to be shown to end-users via mobile app.2. A machine learning algorithm that identifies new demographics and geographies where clients are likely to have the greatest success with new customer acquisition if resources are reallocated. Predictions are determined by learning from the socioeconomic environments that led to users joining historically and recommendations for resource optimization are based on identifying new areas where the socioeconomic environment is similar. Presented this model at a large direct selling event and generated customized “Distributor Insight Reports” for potential customers, which resulted in new revenue sources for DSM.3. A reporting framework for data exploration, analysis, and modeling. Alex developed ETLs to ingest data to Azure Data Lake and access from a Databricks cluster. Reports have been generated with regard to app engagement and external engagement, resulting in comprehensive charts, heat maps, time series plots, and many other data visualizations. Reports have been presented to and shared with key stakeholders.

• Wrote an algorithm inspired by Neural Network logic that creates custom Action Plans for users that complete an online survey. In production, the Action Plans are automatically sent to users’ email addresses in real time.• Created website’s server-side: - built Django backend (Python 2.7x) - created Azure SQL Server with multiple MSSQL databases to interact with backend & log analytics with several advanced APIs• Presented the product model and vision to potential clients/users.• Worked independently and directly under the founder.• Learn more at http://www.indie.biz/ and www.indie.biz/team/

- Solved a wide range of data-centric business challenges for small & medium sized organizations by employing state-of-the-art analytics and machine learning within both structured and unstructured data spaces.- Created a machine learning algorithm that predicts and classifies labels in PDF purchase orders at 98% accuracy in out-of-sample testing.- Developed a NLP-based sentiment analysis program on Java based on real-time tweets from the Twitter API.- Calculated the sponsorship lift for an app using Python, R & MySQL, using data scraped from Google Analytics.- Leveraged existing relationships to bring in new clients to Seattle Data Science.- Engaged directly with clients while leading team members to ensure that our analysis met or exceeded the client’s expectations.

Graded exams & proctored midterms & final exams for upper-division economics courses.

Typical duties included: coordinating the licensing and registration for events; closing and locking up the buildings; communicating with professors and other building patrons to resolve scheduling conflicts; sorting and distributing mail to professors; and restocking supplies in classrooms, conference rooms, as well as break rooms. Because I was rarely on duty at the same time as my supervisors, I had full autonomy to deal with situations out of the ordinary as they may have occur. In most cases, this involved communicating directly with the Seattle Police Department in response to criminal activity. Additionally, I was trained to respond in the case of an earthquake, fire, volcano, or active shooter.