Attentive® is a personalized mobile messaging platform for innovative brands & organizations that can quickly become a top 3 revenue channel. Using real-time behavioral data, Attentive automatically sends engaging text messages to each subscriber at every step of the customer lifecycle. Over 2,000 leading businesses like Sephora, Urban Outfitters, Steve Madden, and more rely on Attentive and see strong performance, like 30%+ click-through rates and 25x+ ROI.

In September 2020, Attentive announced a $230 million Series D investment, led by Coatue.

To learn more about Attentive or to request a demo, visit www.attentivemobile.com.

During my internship at Attentive, I worked as a software engineer within the Customer Success branch of the company.

My main project was building a SlackBot that provided a user-friendly interface to update the company's main SQL database. This project was highly useful because, in addition to eliminating user error, the permission-driven interface enabled a more controlled and role-based access to the database.

Skills: Decision-making; research and analysis; collaborative; browser, server, and database programming

Technology: Git, Selenium, AWS API Gateway, AWS Lambdas, PyCharm, Heroku, Slack API & Incoming Webhooks

During my internship at DecisionNext, I worked on a number of projects:

Bokeh:

I created a user-interaction visualization app. The first part of this task was to research the kinds of third-party tools available out there. I then identified features that would be useful for our team such as:

1.    Making sure users and customers are going where we want them to go

2.    Tracking the least and most used actions

3.    Tracking how frequently a customer uses the app

I then created an app using the Bokeh Library that pulls data from a list of user calls to the API, and visualizes it, with some useful interactive filtering options. I wanted my app to display the various Actions offered by DecisionNext, so I decided on a scatter plot, where each dot represents an action. I also added features to sort actions based on User, Customer, run time, status message, and action type. You can also select multiple users and customers to plot them against each other. I really wanted the app to provide a quick way of seeing how often actions are being used, and by whom.

Selenium:

For this project, I worked with Selenium to create a reusable test suite to automate end to end testing. The tests I wrote performed basic user actions. I used Chrome development tools to help in my task and defined a CI pipeline to automate test runs when changes are pushed to the remote repository. My test suite can be expanded on in the future, by technical and non-technical staff.

Generic File Upload Class:

This project was more Front-end/UI-focused. I replaced current code with a reusable file upload handler supporting the validation of our most common file formats.

Skills: Continuous Integration, Local Development, QA

Technology: Docker, Git, Selenium, Chrome Driver, Visual Studio, PyCharm, Balsamiq, JupyterLab

During my internship with DotAlign, I created an application to analyze customer submitted logfiles. Upon submission, the log files are stitched together to create a single file and a brief report is generated including a summary of errors broken down by version of the app as well as an overview of what the user’s application had been doing. The application was written in such a way that it is easy to add new ways to analyze the logs.

I was responsible for both creating the application as well as researching and ultimately deploying it to Windows Azure Logic App and Azure Functions.

Skills: Continuous Integration, Dependency Injection

Technology: Azure Logic Apps, Azure Function Apps, Azure Queue Storage, Azure Blob Storage, Azure File Storage, Visual Studio 2017, Ninject, Git, TeamCity