Python (Data Analytics) Engineer

Description

About This Role comScore is a leading big data technology company that measures what matters to make crossplatform audiences and advertising more valuable. We are seeking a Data Analytics Engineer to translate large volumes of SAS production code to a Python environment. This Engineer will be responsible for data architecture, data analysis, design, and development of comScores core measurement products. Their work will have a direct impact on driving business strategies for prominent industry leaders. Selfmotivation and strong communication skills are both must haves. You will need to be comfortable working in a fastpaced work environment with shifting priorities, vague requirements, and rapid iterations.
What You'll Do Gather and document requirements from internal customers.
Design architecture and prototype solutions for data processing, methodological, analytical, and statistical projects that span across multiple comScore products.
Build, test, and troubleshoot new features and concepts and integrate into production process.
Validate and analyze output to ensure that all requirements are successfully met.
Exercise your experience in the development lifecycle through analysis, design, development, testing and deployment of this system.
Collaborate with teams in Software Engineering, Operations, and Panel Sciences to deliver timely and quality data. Educate current SAS analysts/developers to internally maintain production, test, and adhoc Python code.
What You'll Need 23 years of full time Python development experience in a professional, production environment using version control (Git required).
Experience in data analysis and problem solving with Python (pandas and numpy).
Experience using SAS preferred. Reading SAS is more important to us than a pure SAS developer.
Deep knowledge of relational databases and methods for efficiently retrieving data.
Ability to think creatively and solve complex problems.
Excellent verbal, written and computer communication skills with strong analytical and troubleshooting skills.
Ability to consistently meet data expectations; holds team and selfaccountable.
Ability to manage change, course correct, and respond decisively.