Data Scientist

AI Revolution: Employee Screening

We are witnessing a pivotal moment in history where artificial intelligence has improved to the point where it can evaluate and screen humans better than other humans. At Shaker International, we are using these advances to change how hiring is done. Join us and work with a highly skilled team of researchers and consultants on some of the most exciting challenges while creating value through building products for some of the best companies. Seize this opportunity to change the world with AI.

The Company: Shaker

Shaker is tackling one of the most exciting data science challenges, predicting success/failure of a person in a new environment. We have great clients (many from the Fortune 50), a great team (35 Ph.D.s and growing), and a long record of success (over 15 years, so tons of data to play with).

The Role: Data Scientist

At Shaker, you’ll be working to spearhead deep learning and machine learning into the field of employee selection. You will be working alongside visionaries in the field, bringing to life the latest and greatest advances in data science by directly building products for our clients. We have had great success using the latest machine learning and deep learning techniques to take our products to the next level. We are looking to you to propel that even further. Specifically, you will be unpacking and researching deep learning (to improve prediction, limit bias, etc.) and productionizing models (running them live on 100ks of people).

Location and Full-time

While we value interns and part-time work, this role is full-time. By responding to this application, you are applying to a full-time role. Also, our headquarters is in Cleveland, OH (along with about 50% of the current employees) but there are Shaker employees located all over the US. If hired you will have the option of relocating to Cleveland or working remote.

Skills:

Machine Learning Deep Learning

Productionizing code

Python and R

Databases

Apply here:

https://goo.gl/forms/DYLjuqRcQvilmWdT2

Job Type: Full-time