This position will focus on future measurement technologies and will play a key role in our upcoming measurement strategy. The team member will work on both statistical research and code development. They will need to design and execute concrete research approaches based on abstract concepts, and then use the results of their research to implement changes into future production methodologies. The team member will need to present research to key stakeholders and collect/implement feedback as necessary. Methodologies are primarily associated with television and digital measurement.
- Design, execute and summarize research based on abstract questions and concepts.
- Provide recommendations and reasoning for rule changes based on research findings.
- Document research plans, results, and conclusions. Share them with auditors as needed.
- Collaborate with stakeholders in various departments (Engineering, Data Science, Technology, etc.). This includes providing status updates, developing timelines, sharing data, executing tests, presenting results, etc.
- Explain complex mathematical and computer science concepts in simple terms to non-technical audiences.
- Configure, deploy, monitor and update a drools engine and some supporting java code.
- Coordinate regular code reviews with team members prior to deployments.
- Degree in Computer Science, Mathematics, Engineering, Statistics or a related field.
- 5+ years of data engineering experience / software development experience
- Expert knowledge of Python, Spark, Scala
- Expert knowledge of the Hadoop ecosystem
- Experience with Java, Drools
- Experience with AWS
- Experience with Gitlab, Airflow
- Strong knowledge of ETL pipelining and data warehousing
- Exceptional problem solving skills
- Excellent oral and written communication skills. Well organized and capable of handling multiple mission critical projects simultaneously while meeting deadlines
- Self-motivated and an ability to handle multiple competing priorities in a fast-paced environment
- Manage projects consisting of cross functional teams including data science, engineering, and product leadership