About the job

Google's leadership team hand-picks thorny business challenges, and members of Biz Ops work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

In this role, you will provide data-driven insights and problem-solving support for the g Tech Ads organization. You will be focused on solving strategic and operational problems by working with large amounts of data that reside on the internal systems, conceptualizing and building problem-solving solutions, generating data insights, translating them into actionable recommendations, and influencing important business decisions.

Responsibilities

• Use data to conduct data-oriented analysis, architect metrics, synthesize information, solve problems, and influence business decision-making by presenting insights and market trends.

• Design and implement various integrations between business objectives, and design and build strategies that support these business systems.

• Conduct strategic analysis, optimize business performance, and deliver execution within product and function.

Minimum qualifications

• Bachelor's degree in Engineering, Math, Quantitative Science, or related technical field, or equivalent practical experience.

• 3 years of experience working in data analytics, consulting, data science, engineering, or a technical operations role.

• 3 years of experience in statistical problem solving and analyzing data sets using SQL or comparable coding language (e.g. Python, R, Java, C++).

Preferred qualifications

• Experience in a Sales or Customer Service environment.

• Understanding of engineering practices; e.g., development of BRDs/PRDs/Design Docs, checking in and reviewing code, etc.

• Knowledge of data analysis tools (R, Python) and techniques (experimental analysis, predictive modeling, machine learning, etc.).

• Excellent problem-solving skills, with ability to synthesize data into useful formats and bring actionable insights through effective communication.