Your organization wants to compete more effectively in the data economy.
Every digital transformation is based on a data transformation--more effective collecting of data, modeling of data, and making business decisions based on data. However, building organization-wide data literacy, and hiring data literate professionals, is challenging.
Your organization is also committed to building a more diverse workforce.
You recognize that diverse minds build better products. And that companies, via corporate social responsibility mandates, are one of the most powerful platforms for social change today. However, hiring under-represented minorities in STEM-related jobs is challenging for almost every firm.
Now, for the first time, there is a turnkey solution for both goals: hiring data-literate professionals and building diverse workforces.
Data Science For All / Empowerment
"DS4A" / Empowerment is a novel program to create equal access to the jobs of tomorrow. It provides 100% free technical training in data & analytics for under-represented minorities. Training is instructor-led, delivered by professors from Ivy League universities.
Over 8,500 people applied to the program, and the top 6% were selected for 500 available slots in the first cohort, which began on October 24. The class is 60% black or African American, 30% Latinx or Hispanic, 15% LGBTQ+, with a long-tail of other under-represented talent, including military vets and refugees. The class is majority female.
Admitted participants (“Fellows”) receive 4 months of training. Half of the 500 Fellows are currently in school, whether at the undergraduate, graduate, or PhD level, and the other half are early-career working professionals. See video stories of some DS4A / Empowerment Fellows here.
The key skill participants learn during training is how to connect data to business: how to pose the right technical questions, build commercial solutions, and present solutions to business stakeholders.
The DS4A / Empowerment Fellows represent the most diverse group of data-literate professionals ever assembled.
For organizations seeking to build diversity and advance their analytics capabilities, our Fellows are a vetted, trained, diverse pipeline “as a service”. We are building the first ever marketplace for hiring diverse data & analytics professionals.
Our Corporate Partners include blue chips from healthcare, technology, financial services and other industries, companies such as Anaplan, Match Group, Dana-Farber Cancer Institute, Gilead Sciences, Two Sigma, and Citadel.
Organization-wide Data Literacy
Organizations building their data capabilities often make one key mistake: they hire data professionals only within their technology or data orgs. This is a significant lost opportunity.
That’s because data is not a vertical--it is not one job family. Instead, data is a horizontal--it is a skillset that cuts across an increasing number of jobs in every department. A marketer is a better marketer with data skills. A product manager is a better product manager with data skills. And so on for operations, engineering, sales, management consulting, etc.
In fact, the most valuable data professionals are those who can combine data skills with domain expertise--those who have expertise in (for example) marketing, but who also know enough data science to understand and conduct a rigorous A/B test.
When building your organization-wide data literacy, it pays to hire data-literate professionals in every department: from marketing to analytics to operations to human resources. These are the marketers, product managers, and engineers of tomorrow. They help unlock business opportunities leveraging data & AI in every department, and create a culture of data literacy throughout your organization. A list of example roles across the org where you should look for data capability is here.
We believe that our diverse cohort has both the wide exposure and well-grounded data fluency to fill these roles. Our Corporate Partners across industries hire them for critical jobs, and we welcome you to join us to hire and promote your roles as well. Together we can make data science for all.
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