Business Data Scientist, gTech Ads (English, Portuguese)

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

• Ability to communicate in English and Portuguese fluently to engage with clients in the region.

Preferred qualifications:

• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

• Experience leveraging data insights into storytelling for business stakeholders.

• Experience delivering insights from ML to customers (problem scoping/definition, modeling, interpretation).

• Experience using or deploying digital analytics and measurement solutions.

• Industry experience, including: retail, financial services/retail banking, insurance, telecommunications, automotive and Consumer Packaged Goods (CPG).

• Understanding of the statistical algorithms such as Bayesian models typically used in Marketing Analytics and MMMs.

About the job:

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

The Google Customer Solutions (GCS) Partner Engineering team in gTech Ads consists of engineers and data scientists providing custom solutions and technical consulting to Google’s partners.

As a data scientist, you will combine consulting and technical skills to solve complex marketing challenges for our largest advertisers. You will apply best practices and Google’s ML capabilities to execute gTech’s goals, delivering innovative, high-impact solutions through cross-functional collaboration.

In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration and more). Responsibilities:

• Lead Data Science client engagements focusing on marketing effectiveness and portfolio management, utilizing deep expertise in Marketing Mix Models (MMMs), ML, and statistics.

• Partner with customers, sales, and internal teams to unpack problems and build end-to-end statistical modeling frameworks, translating complex data into actionable strategic insights and co-presenting recommendations to integrate into business processes.

• Collaborate with Product/Engineering teams to increase and optimize capabilities of our Applied DS team, employing methods which create opportunities for scale, proactively helping to drive innovation.

• Develop comprehensive understanding of Google data structures, and metrics, advocating for product changes where needed.

• Engage key stakeholders to evaluate data and model readiness, successfully scaling proof-of-concepts into comprehensive solutions.