Synthetic data project framework

Our company is interested in creating frameworks / templates for our pilot projects with social impact clients. Impact of this work is to maintain efficient operational execution in how we structure our client work. We would like to collaborate with students to provide cohesive, appropriate details relative to the pilot project scaffolding from our Data Scientists. Students will write technical statistical documentation on methodologies and write code (likely in Python, using Jupyter and/or Marimo notebook) so we can achieve a fulsome pre-pilot understanding of the workflow involved. This will involve several different steps for the students, including: Working with Data Scientist guidance to write code that assesses initial data type, structure, etc, especially on determining appropriate analytical tooling for client data use case categories Expanding on baseline Data Scientist framework document for synthetic data 'utility' metrics, i.e. how useful to a given statistical model the synthetic data is Completing all above in analytical objectives including but not limited to dimension reduction, relationship analysis, and clustering

Synthetic data AI/ML App

Our company is interested in researching the different options for synthetic data generation, with Python libraries as a starting point. Applications of this work span the variety of services we provide in data creation, management, and analysis to potential clients in the social impact sector. We would like to collaborate with students to research how best to compare the available Python packages for synthetic data generation, which typically involves use of statistical methods alongside generative models (i.e. generative adversarial networks, variational autoencoders) and sometimes conditional generative models. Students will create a summative white paper style document as well as use that as a basis for a Jupyter notebook that rigorously and holistically demonstrates the findings. This will involve several different steps for the students, including: Conducting background research on how existing Python synthetic data libraries were created and set up. Analyzing our current services offerings in data creation, management, and analysis. Researching how existing Python synthetic data libraries could be applied for potential clients. Developing a summative white paper that provides unique outcomes or insights into our application for potential clients. Providing a Jupyter notebook that can be used to guide our exploration of next steps for potential clients.

Synthetic data AI/ML App

Our company is interested in building upon our synthetic data application. Impact of this work spans the variety of services we provide in data creation, management, and analysis to potential clients in the social impact sector. We would like to collaborate with students to simulate different tabular data scenarios by needs specific to each sub-sector we serve, i.e. philanthropy, impact investing, think tank, advocacy, higher education. Students will write code and documentations to explore 2-3 common, tabular dataset scenarios per sub-sector that our company can use as reference points for our application's back-end processing tasks. This will involve several different steps for the students, including: Developing familiarity with Python synthetic data libraries Building intuition on dataset structures typical in social impact sub-sectors Evaluating then prioritizing options for building the app back-end with a zero-trust architecture model Writing clean code and requisite technical documentations

Synthetic data startup website

Our company is interested in further developing design and code for our client-facing website. Impact of this work is to continue our consistent messaging with clients in the social impact sector. We would like to collaborate with students to refresh the content, organization, and call-to-actions of our website. Students will work in Framer so we can efficiently put our best forward for website visitors. This will involve several different steps for the students, including: Refreshing the custom graphics for each of our core services: Synthetic Data Generation, Data Management, Data Analysis Adding 'tabs' / pages option to redirect to "RESOURCES", plus the "RESOURCES" page itself Adding a footer to all website pages that links to: the pages "SOLUTIONS", "ABOUT US", "CONTACT US", "RESOURCES"; our social media accounts via platform icons; and a call-to-action "Join our email list" button Implementing the mailing list call-to-action pop-up within 30 seconds of someone entering the website