- Serve as the team expert in machine learning, learning, Bayesian analysis, and other areas of mathematical statistics
- Drive the collection and manipulation of new data and the refinement of existing data sources.
- A strong understanding of the differences between inferential and predictive models and experience applying methods in both areas
- Translate complex problems and solutions to all levels of the organization.
- Drive innovation of the statistical and machine learning methodologies and tools used by the team.
Qualifications/Requirements:
- Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
- 5+ years of combined experience in advanced analytics in industry or research.
- Expert level knowledge of machine learning. Ability to define the direction for a project and select appropriate methods and tools. Up to date knowledge of recent advancements
- Working experience with deep learning, particularly in the areas different form the computer vision. Strong experience with deep learning using TensorFlow.
- Experience implementing scalable, distributed, and highly available systems using Google Could Platform.
- Experience with Google AI Platform/Vertex AI, Kubeflow and Airflow.
- Proficient in Python. Java or Scala is a plus.
- Experience in data processing using SQL and PySpark.
Desired Characteristics:
- Working experience with commercial recommender systems or a lead role in an advanced research recommender system project.
- Experience with reinforcement learning based systems.
- Experience with multi-billion record datasets and leading projects that span the disciplines of data scienceand data engineering
- Knowledge of enterprise-level digital analytics platforms (e.g. Adobe Analytics, Google Analytics, etc.)
- Experience with large-scale video assets
- Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools