Show HN: A data science fellowship to solve the world’s toughest problems

To get more exposure, consider posting the fellowship to these subreddits:

http://www.reddit.com/r/datascience

http://www.reddit.com/r/datasets/

http://www.reddit.com/r/statistics

http://www.reddit.com/r/machinelearning/

If you have not already, I would recommend reaching out to these companies to sponsor: Cloudera, Palantir, New Relic, Tableau, Domo.

This is an awesome initiative. It's good to see an organization using and promoting data science for something other than "optimizing click ads." Kick some ass guys!

Hi Shoyer, one of the founders here! For our fall fellowship, support will likely be in the range of $4,000-6,000 per month based on experience. We also provide a fellowship house in San Francisco for our fellows to live in.

Hi ajiang, This is a great initiative. Glad to see Data Science knowledge put to use for noble causes. I am a mentor in a Data science/analytics program based in Bay Area where we help professionals looking for a career change to data science. We are always hunting for interesting projects for them to work on. Would love to have them work on real projects with noble goals. Love to connect to discuss this possibility. If interested, please ping me. You can find my email in my profile. Thanks.

I appreciate what you guys are trying to do but I can't seen many mathematicians or statisticians applying for this unless you provide a little more information about what these "hard" problems are.

Honestly it reads like your offering basic in training in a a random selection of tools and then hoping some non profits present a problem with nice clean data that can be solved through application of a few methods from scikit.learn.

If you wan't to attract math people my suggestion would be to identify a few intriguing and hard problems a head of time and taking applications specifically for them...you can always suggest a change if you think an applicant would be better suited to a different one. Providing intriguing problems that might match up with peoples pre existing research interests is key...there is lots of room for cross pollination and growth but a bayesian statistician is going to be much more intrigued by something that might benefit from a hierarchical model then something that needs ODE's or online convex optimization.

Worse 4-6 months might not even be enough time to formulate a problem that needs a solution and get the required data in place. Non profits are generally extremely overworked and take a long time to do things. They will not have their data in anything resembling a database or standardized format...think short hand notes in word files if you're lucky. Identifying people and data you can work with on this end a head of time is key.

For the record I work for a non profit analyzing complex diseases and my background is in math. I've also sat on the board of and been involved in a few other non profits.