About the Role:
The Data Science Engineering team writes the math and software that sit at the heart of AdRoll’s real-time bidding technology, our core product. Our software runs over hundreds of terabytes of data daily to produce its models, which are then subsequently queried billions of times by hundreds of servers.
Current members of Data Science Engineering have a passion for not only mathematics, but also technology. If you join our team, you will have the opportunity to stay on the cutting edge of research and then to put this research to practical use by building your own software and infrastructure systems. When you push out your code, you will be able to see the results of your efforts ripple throughout our systems in real-time.
Moreover, AdRoll Engineering is broken out into small teams that have significant autonomy. We like to think of Data Science Engineering as a ‘startup within AdRoll.’ You will design your systems as you see fit, own your code, and your work will have a very direct, measurable impact on AdRoll’s core metrics.
Data Science Engineering is a small team with a variety of concurrent projects. Your interests dictate what projects you will tackle. The common thread among all projects is that they require a high level of mathematical sophistication and engineering prowess, due to the scale of our data.
Current projects include:
Enhancing our machine learning software with the latest in machine learning algorithms
Employing machine learning and statistical modeling over our petabytes of data to generate new features to feed into our bid-time predictions
Creating systems that monitor inputs and performance on a real-time basis to inform engineers when unexpected changes arise.
Performing automated market analyses to dynamically react to changing market conditions
Responsibilities:
Discover new predictive insights in our dataset
Design systems that regularly compute new predictive models
Read and conduct research to develop mathematical solutions to our most pressing problems
Engineer to put your research into practice
Ownership of a system that is the core of our intelligence products
