We’re looking for an exceptional Director of Data Science to lead a cross-disciplinary team focused on the development of our real-time bidder, one of the most exciting and important products within. The system powering this product must deal with 100,000’s of requests per second and presents unique engineering challenges. In addition, the bidder requires use of machine learning models that are trained in batch and then used to power decision making in real-time.

Impact You Will Make: 

• Lead a group of Data Scientists and Machine Learning Engineers to successfully deploy elegant solutions
• Foster a culture of collaboration and excellence
• Continue the buildout and improvement of our ML infrastructure and platform
• Develop and mentor team members professionally and technically
• Identify hiring needs and work with our talent team to find the best people
• Collaborate closely with our product team to understand customer needs and build ML solutions that meet them
• Work alongside our data and engineering leaders to build new features and capabilities
• Develop best practices for ML and ML engineering, covering data processing, monitoring, experimentation, etc

Who you are:

• PhD in machine learning, statistics or comparable field, or MS/BS degree with significant industry experience.
• 6+ years of data science/machine learning experience applied to business problems
• 4+ years of experience leading machine learning teams
• Diverse exposure to many different Machine Learning and modeling techniques such as NLP or deep learning as well as traditional modeling techniques
• Experience with modern ML development stack, open source libraries and hosted ML services (e.g. Tensorflow, PyTorch, NumPy, AWS Sagemaker, etc.).
• Experience with ML engineering, able to propose and design ML solution, comfortable reviewing production code
• Experience with MLOps, comfortable designing and operating a system that can deploy and manage ML models in production

The following experience would be a plus:

• Knowledge of distributed tools and frameworks, like Spark/Hadoop for large scale data processing
• Ad tech and/or mobile space