Analyst, Advertising Analytics

Key Skills

AWS, Big Data Technology, Data Analytics, Data science techniques, Design, ETL frameworks, Github, Google Cloud Platform (GCP), Looker, Machine learning techniques, PowerBI, Python Programming, R Programming, SQL, Tableau

Job Description

We are looking for analytical talent to turn passion for data and support of world-class journalism into decision-making insights. 

As part of the Data and Insights Group (DIG), you will join a large community of accomplished analysts who partner with Product, Engineering, Design, Data Science, and PMO teams across the business. You’ll work with our Digital Advertising Team to build and understand audience segments across all NYT surfaces, establish data quality practices, and create complex and reliable data marts. You will solve technical problems that require investigation while maintaining awareness of broader business contexts and following legal and ethical standards around data privacy. You will report to the Senior Manager, Advertising Analytics.

Responsibilities:

• You will create, document, improve, and maintain complex data pipelines using SQL and ETL tools

• You will support analyses to be presented to high-level partners in slide decks and memos to guide team strategy

• You will develop dashboards to expand access to data and analytics

• You will collaborate with company partners to understand the business and develop data-driven insights that are both strategic and operational

• You will participate in and sometimes lead all phases of analytic work: from problem definition to representation of results

Basic Qualifications:

• 1+ years of experience working with data teams to deliver analysis

• Proficiency in SQL and experience working with relational databases

• 1+ years of experience working with dashboarding tools such as (Mode, Tableau, Power BI, Looker)

Preferred Qualifications:

• 1+ years with a big data environment or distributed data system like Google Cloud Products (GCP) or Amazon Web Services (AWS)

• Experience in Python or R

• Familiarity with machine learning principles

• Comfort with version control (Github, code review)