* I worked within the Marketing team in Visa Functions and Products (VFP) under Global Data Solutions. My responsibilities involve data science, machine learning, and analytics for internal stakeholders of the company.* Member of the VFP Tech Committee. Work with Data Engineering and Data Platform team to ensure the VFP team is productive with the current technology stack.

* Responsible for developing, deploying, and maintaining machine learning projects and infrastructure.* Worked with the CTO and Director of Engineering to oversee data strategy.* Developed data strategy within the organization, including data quality and evaluation* Created propensity model for recommending optimal medical services to patients* Constructed model deployment pipeline within Amazon SageMaker* Designed multiple systems on AWS with Terraform across multiple environments

Hired as MeetMindful's first data scientist to build & maintain data science applications, models, reports, and systems. My work included recommendation systems, natural language processing, and how this relates to human behavior within online dating. I oversaw and maintained all machine learning projects in production.Additionally, I was responsible for maintaining the cloud infrastructure of the company. This included architecture evaluation, encapsulation with Docker, and AWS solution architecture.* Created recommendation system for 1.4+ million users.* Automated paid marketing acquisition reporting, reducing annual cost by $25,000.* Increased mutual match rate from 8% to 22% during revised product launch in local markets.* Improved user moderation model by 130%, reducing human review by 8 hours per day.* Optimized AWS infrastructure, reducing monthly spend by 45%.* Created cohort scoring model to gauge paid acquisition quality.* Evaluate user retention through statistical analysis.* Analyzed free text responses of users who deleted and downgraded their accounts, and provided recommendations for user retention.* Built Latent Dirichlet Allocation model for historical persona evaluation.

Supported data processing during the night, leading up to the availability of analysis at the start of the business day for clients.Developed ETL processes with development teams for each client.Created virtual machine instances of client environments for on-boarding new hires.Participated in internal data science competition; analyzed 300 gigabytes of data to predict the probability of advertisements being clicked.

Proved psychometric project results can be predicted with data science.Evaluated 21,000 person National Institute of Health survey with 2,700 variables.

Facilitated learning for 70 students.Provided knowledge on the software program Alteryx.Suggested advice for team data models during the class Kaggle competitions.

Supported Trade Promotion Effectiveness (TPE) Improvement Project.Assisted in creation of reporting application for product promotion optimization.Created predictive analytic models for cannibalization and price elasticity.Successfully proved existence of product segmentation trends using data science.

Expanded group size from 1 member to 174 member over 2 years.Facilitated the teaching of the music production software Ableton Live. Developed community of musicians interested in broadening their skill set.Proactively contacted and maintained relations with Ableton.

Filled the position when the previous member elected to drop position mid term.Wrote memos and newsletters of the monthly activities within the fraternity.Established communication with brothers outside of the fraternity, including graduates and university alumni.

Organized events devoted solely to helping the community. Coordinated fundraiser to help recover possessions lost in a sorority house fire.

Recruited the largest pledge class of the colony’s history.Assisted in a membership increase of nearly 100%, from 13 to 23 men.Responsible for directing events during Spring Rush 2012, including open house.