Data are becoming the new raw material of business
The Economist

JUST Capital and The Data Incubator Challenge

Data Science For Social Good (1)

 

Today, we’re excited to announce that we’re teaming up with JUST Capital to help crowd-source data science for social good.  The Data Incubator offers a free eight-week data science fellowship for those with a PhD or a masters degree looking to transition into data science.  As a part of the application process, students are asked to submit a data science capstone project and the best students are invited to work on them during the fellowship.  JUST Capital is helping providing data and project prompts to harness the collective brainpower amongst The Data Incubator fellows to solve these high-impact social problems.

  • These projects focus on applied data science techniques with tangible impacts on JUST Capital’s mission.
  • The projects are open ended and creativity is encouraged. The documents provided, below, are suitable for analysis, but one should not shy in seeking out additional sources of data.

JUST Capital is a nonprofit that provides information and rankings on how large corporations perform on issues that matter most to the public. We give individuals a voice on what really matters to them, and evaluate how companies perform on those issues. By providing the right knowledge and making it easy to access and understand, we believe capital will flow to corporations that are more JUST, ultimately leading to a balanced business world that takes into account human needs that are so often neglected today. The meaning of JUST is defined by the American public as fair, equitable and balanced. In 2016, JUST Capital surveyed nearly 4,000 Americans from all regions and walks of life, in its second annual Poll on Corporate America. The issues identified by the public form the basis of our benchmark — it is against these Drivers and Components that we measure corporate performance. The most important factors broadly relate to employees, customers, company leadership, the environment, communities and investors.

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How Employers Judge Data Science Projects

mark-516277_960_720One of the more commonly used screening devices for data science is the portfolio project.  Applicants apply with a project that they have showcasing a piece of data science that they’ve accomplished.  At The Data Incubator, we run a free eight week fellowship helping train and transition people with masters and PhD degrees for careers in data science.  One of the key components of the program is completing a capstone data science project to present to our (hundreds of) hiring employers.  In fact, a major part of the fellowship application process is proposing that very capstone project, with many successful candidates having projects that are substantially far along if not nearly completed.  Based on conversations with partners, here’s our sense of priorities for what makes a good project, ranked roughly in order of importance: 

  1. Completion: While their potential is important, projects are assessed primarily based on the success of analysis performed rather than the promise of future work.  Working in any industry is about getting things done quickly, not perfectly, and projects with many gaps, “I wish I had time for”, or “ future steps” suggests the applicant may not be able to get things done at work.
  2. Practicality: High-impact problems of general interest are more interesting than theoretical discussions on academic research problems. If you solve the problem, will anyone care? Identifying interesting problems is half the challenge, especially for candidates leaving academia who must disprove an inherent “academic” bias.
  3. Creativity: Employers are looking for creative, original thinkers who can identify either (1) new datasets or (2) find novel questions to ask about a dataset. Employers do not want to see the tenth generic presentation on Citibike (or Chicago Crime, Yelp Restaurant Ratings data, NYC Restaurant Inspection DataNYC Taxi, BTS Flight Delay, Amazon Review, Zillow home price, or beating the stock market) data. Similarly, projects that explain a non-obvious thesis supported by concise plots are more compelling than ones that present obvious conclusions (e.g. “more riders use Citibike during the day than at night”). Employers are looking for data scientists who can find trends in the data that they don’t already know. Continue reading
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Data Sources for Cool Data Science Projects Part 6

startup-593324_960_720Links to Part 1Part 2Part 3Part 4, Part 5

At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are a few cool public data sources you can use for your next project:

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Data Sources for Cool Data Science Projects: Part 5

computer-1185626_960_720Links to Part 1Part 2Part 3, Part 4

At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are some more cool public data sources you can use for your next project:

Continue reading

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Data Sources for Cool Data Science Projects: Part 4

student-849825_960_720Links to Part 1Part 2Part 3

At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are some more cool public data sources you can use for your next project: Continue reading

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Data Sources for Cool Data Science Projects: Part 3

student-849822_960_720Links to Part 1, Part 2

At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are some more cool public data sources you can use for your next project: Continue reading

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The Data Incubator Featured in The Next Web

Today, The Data Incubator was featured in The Next Web. The article, “Data Incubator opens a West Coast campus to groom the next generation of data scientists,” can be found below and on The Next Web here.

 

golden-gate-bridge-388917_960_720Data Incubator, an East Coast fellowship program, is expanding to the West Coast with a new office in San Francisco. Its goal is to prepare highly qualified scientists and engineers for work as quants or data scientists.

The Bay Area campus has already accepted 10 fellows for its inaugural class.

Data Incubator takes fellows with “most of the advanced education and foundational knowledge required to pursue a professional data science role.” Those with Masters degrees or PhDs in computer science, mathematics, social science, statistics, and physics are best positioned to be accepted. Continue reading

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Data Sources for Cool Data Science Projects: Part 2

startup-849804_960_720Link to Part 1

At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are some more cool public data sources you can use for your next project: Continue reading

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Data Sources for Cool Data Science Projects: Part 1

startup-594127_960_720At The Data Incubator, we run a free eight week data science fellowship to help our Fellows land industry jobs. Our hiring partners love considering Fellows who don’t mind getting their hands dirty with data.  That’s why our Fellows work on cool capstone projects that showcase those skills.  One of the biggest obstacles to successful projects has been getting access to interesting data.  Here are a few cool public data sources you can use for your next project: Continue reading

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How to Prepare for The Data Incubator

business-1989131_960_720At The Data Incubator, we receive thousands of applications to join our data science fellowship. Our admissions bar is very high and we are often asked:

                        What can I do to prepare for the fellowship application process?

Here are five important skills to develop and some resources on how to help you develop them. While we don’t expect our applicants to possess all of these skills, most applicants already have a strong background in many of them. Continue reading

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