The Platform ML team is a group of full-stack data scientists charged with building core products for the measurement, optimization, and automation of marketing, publishing, and product functions across this vast portfolio. These ML products are vital to Zynga’s success, informing all facets from operational and executive decision-making.
As a full-stack data scientist, you will use your expertise across machine learning, software engineering, and business analytics to build end-to-end solutions that scale across our broad portfolio, embody CI/CD standard processes for continuous operations/improvements, and provide prescriptive actions to some of the most exciting problems in the mobile gaming space and beyond. You will be entrusted with key initiatives and given a fair amount of autonomy, so it is critical that you bring technical excellence, a mind for architecture, and a mature sense for timelines to this role.
Responsibilities:
- Use our modern tech stack, AWS (Redshift & Kinesis), Databricks and PySpark, Airflow, and Tableau to develop innovative tools
- 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
- Providing inventive thought leadership in the architecture of our pipelines
- Design and develop in a CI/CD environment
Required Skills and Experience:
- A 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 and the ability to apply that knowledge broadly across our various data pipelines to improve efficacy and efficiency
- Experience crafting large-scale ML pipelines using technologies such as AWS tools, Databricks, and Airflow. Proficiency in SQL and Python is needed
- Full-stack knowledge, especially around software-engineering principles such as modularity, automated testing, and documentation
- 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
What We Offer You:
Zynga offers a world-class benefits package that helps support and balance the needs of our teams. To find out more about our benefits, visit the Zynga Benefits site
