Fellowships & Jobs


Fellowships and Grants

The Data Incubator Fellowship

Program: The Data Incubator is an intensive 8 week fellowship that prepares masters students, PhDs, and postdocs in STEM and social science fields seeking industry careers as data scientists. The program is free for Fellows and supported by sponsorships from hundreds of employers across multiple industries. In response to the overwhelming interest in our earlier sessions, we will be holding another fellowship.

Who Should Apply: Anyone who has already obtained a masters or PhD degree or who is within one year of graduating with a masters or PhD is welcome to apply. Applications from international students are welcome. Everyone else is encouraged to sign-up for a future session.

Locations: In addition to the below in-person locations, we will have a remote online session:

  • New York City
  • San Francisco Bay Area
  • Boston
  • Washington, DC.

Dates: All sections will be from 2018-09-10 to 2018-11-02.

Application Link: https://www.thedataincubator.com/fellowship.html?ch=rec&ref=r71e79d456e27

Data Science in 30 minutes: Learn how to build a data-science project in our upcoming free Data Science in 30-minutes webcast. Signup soon as space is limited.

Learn More: You can learn about our fellows at The New York Times, LinkedIn, Amazon, Capital One, or Palantir. To read about our latest fellow alumni, check out our blog. To learn more about The Data Incubator, check us out on Venture Beat, The Next Web, or Harvard Business Review.

The Hertz Foundation

Hertz Fellowship Application

The annual competition for Graduate Fellowships begins with the application period which opens each year in August at which time a deadline consistent with those of NSF and other fellowship granting organizations will be posted. Only those applications which are complete, with all supporting materials and documents provided (including Reference Reports) by the posted deadline will be assured of full consideration by the Foundation. Untimely or incompletely-submitted applications will be entertained only at the Foundation's discretion and convenience.

Each year's competition concludes at the end of the following March, at which time the Foundation's Board of Directors determines the most highly qualified Fellowship applicants and the number of new Fellowships which available resources will be able to support.

The next Hertz Fellowship Application due dates for academic year 2019 - 20 are:

Application opens: August 15, 2018 
Deadline to submit application: 
October 24, 2018 
References due by: 
October 26, 2018

DEADLINE FOR SUBMISSION is Oct 24, 2018- 11:59 pm, Pacific Time

Reference Reports must be received by the Foundation by Oct 26, 2018

 To apply for the Fannie and John Hertz Foundation Graduate Fellowship, please go to the Electronic Application.

Download the Application Poster here.

Frequently Asked Questions


Data Engineer/Scientist Intern

Data Engineer/Scientist Intern

Motive Interactive Inc. is a mobile advertising platform that build performance solutions
for advertisers, publishers and agencies. Founded in 2003, Motive Interactive has
delivered user acquisitions and app-platforms that engaged robust target audiences and
ranked in the top 3 effective advertising partners, only succeeded by Twitter and
Google. We are looking for a Ph.D. candidate or similar degree in one of the dataoriented
principles to intern with us. This internship could be transferred into a
permanent position in the future.

• Use data pre-processing methods including ETL, schema/data translation and
integration with filtering to transform big data sets into data warehouses and
analytics platform
• Work with stakeholders including Data Science, Analyitics, Product and Business
teams to assist data related technical issues and support their data infrastructure
• Verify third party data and assemble large, complex data sets that meet business
• Do ad-hoc analysis and present results
• Work with engineering team to expand and optimize our data and data pipeline
architectures, as well as data flow and collection for cross-functional teams

• A strong understanding of predictive modeling
• Practice in machine learning theory, data structures and algorithms
• Solid foundation in statistics, regression, correlation, etc..
• Solid background in data analytics
• Good working SQL knowledge and experience working with relational database
• Basic understanding of ETL mechanism
• Good scripting and programming skills. Python skill is highly preferred.
• Knowledge of data visualization and related tools.
• Excellent communications
• Passionate in learning
• Education: Ph.D candidate in Computer Science, Statistics or related technical
• Nice to have:
-Experienced in any of the version control system (Git, perforce, etc.).
-Understanding of Unit testing and debugging protocols
-Experience in Amazon Web Service (AWS) or any other cloud platforms
-Familiar with common data engineering tools such as R, Hadoop, NoSQL