The company is looking to build core products for the measurement, optimization, and automation of marketing, publishing, and product functions across its vast portfolio.
Requirements
- Strong statistical background building sophisticated models that can reasonably describe actual underlying data generation processes
- Experience with Bayesian modeling preferred
- Experience exploring and implementing innovative ML/AI methods
- Experience crafting large-scale ML pipelines using technologies such as AWS tools, Databricks, and Airflow
- Proficiency in SQL and Python
- Full-stack knowledge, especially around software-engineering principles such as modularity, automated testing, and documentation
Responsibilities
- Develop innovative tools using modern tech stack, AWS (Redshift & Kinesis), Databricks and PySpark, Airflow, and Tableau
- Apply statistical methodologies to evaluate performance and account for uncertainties in major initiatives
- Implement groundbreaking machine-learning pipeline technologies to scale and propel the marketing, publishing, and product functions
- Provide inventive thought leadership in the architecture of pipelines
- Design and develop in a CI/CD environment
Other
- Strong mentorship skills
- 4+ years of work experience in data science, machine learning or analytics roles
- BS in Computer Science, Math, Statistics, Economics, or other quantitative field; Masters or PhD strongly preferred
