Business and Marketing Data Scientist, gTech

Key Skills

Python Programming, SQL, Data science techniques, R Programming

Job Description

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; Pittsburgh, PA, USA.

Qualifications

Minimum qualifications:

• 3 years of experience in Data Science or a related field.
• Experience in a customer-facing role translating technical concepts and solutions to non-technical and executive audiences.
• Experience in statistical methodology and computational programming.
• Experience in Marketing Analytics and/or Software Development, including using SQL, R, or Python.

Preferred qualifications:

• Master's or advanced degree in a quantitative field such as Statistics, Engineering, or Sciences, or equivalent practical experience.
• Ability to craft engaging/compelling narratives in verbal and written communications for internal/external clients (i.e. executive stakeholders).
• Ability to manage multiple projects with competing priorities.
• Excellent organizational and project management skills.

About the job

In this role, you will work cross-functionally with product, operations, engineering, and marketing stakeholders to facilitate data-informed business decisions, ingenuity, product improvements, and business solutions.

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.

To learn more about gTech, check out our video.

Responsibilities

• Work on data modeling, metric development, data prototyping, and insight generation using statistical techniques and machine learning.
• Work with engineering, operations, and marketing teams to identify areas to focus effort.
• Solve ambiguous problems and discover insights that drive operational, product, and marketing excellence.
• Ensure users have excellent product and service experiences.