Responsibilities
- Research and implement methods for demographic prediction for measurement and optimization use cases.
- Conduct detailed data analysis and quality assessment for available data assets.
- Translate new methodologies into functional modules, including unit tests and quality control checks.
- Provide data-driven recommendations for promoting enhancements to production, including client-focused simulations.
- Identify root causes and solve any bugs or quality escapes.
- Contribute detailed documentation of new methodologies, research findings, and best practices.
- Work with cross-functional team members to test and push methodology updates to production.
- Execute projects from beginning to end including design, execution, and summarization.
- Explain complex data science concepts in simple terms to non-technical audiences.
Key Skills
- Bachelor’s degree in a quantitative programming field, such as computer science, data science, engineering, statistics, mathematics, biological/physical sciences, etc.
- 2-3+ years of professional work experience in Statistics, Data Science, and/or related disciplines.
- Strong Python skills.
- Experience with sophisticated data mining & modeling solutions and the tools that support them (e.g. Scikit-learn, PyTorch, PyMC3).
- Experience with relational and distributed database systems with expertise in tools such as Spark, Presto, and other SQL-based querying engines.
- Familiarity with DevOps tools and CI/CD workflows including Git.
- Well organized, self-motivated and an ability to handle multiple competing priorities in a fast-paced environment.
Desired Skills
- Advanced degree in Statistics, Data Science, Computer Science or other related field.
- Experience with implementing and managing software in cloud-based environments such as Azure, AWS, or GCP.
- Experience with task orchestration frameworks like Airflow.
- Domain expertise in content measurement and/or ad tech.

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