Business Data Scientist, Machine Learning

Google • Mountain View, CA

113d • $166,000 - $244,000

About The Position

The Global Business Strategy and Operations team is part of the Go-to-Market organization that makes sure Google's business pursues the best strategy and executes flawlessly. Team members are exceptional in business strategy and operations, are problem-solvers and strategic, yet highly pragmatic and results-oriented. This team architects the future of Google's global ads business. The function drives Go-to-Market strategy and analytics, operational efficiency and productivity, risk and compliance, Chief Business Officer and Chief of Staff team, and ads policy strategy. The Data, Insights, and Analytics (DIA) partners with various Global Business Strategy and Operations team members to drive the best decisions possible with data. We build creative and novel Machine Learning (ML) solutions and analyses to drive strategy. We help our organization make nuanced, smart, and difficult decisions to ensure the Ads Business continues to grow. In this role, you will be significantly improving how customers are assigned to the most optimal sales channel, as our current manual decision model, while nuanced, is limited by historical data and a narrow understanding of what drives customer performance. You will be tasked with developing a causal ML model to automate and enhance these assignments, while also uncovering new data patterns that could revolutionize how our business manages clients. You will need to be a strategic thinker, using your business and product judgment to guide our data strategy. Your problem-solving skills will be key to ideating, discovering, and integrating hundreds, if not thousands, of data signals, ensuring they are perfectly structured for our causal ML problem.

Requirements

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Nice To Haves

• Experience designing and implementing causal ML models.
• Experience designing and building large datasets for ML modeling.
• Experience with statistical modeling packages.
• Excellent presentation skills.

Responsibilities

• Develop core dataset and signal repository, using SQL or other scripting language, for Machine Learning.
• Develop expansive dataset that describes the Google Ads Customer, in as much detail as reasonable, that will enable us to establish causal effects from our business efforts.
• Investigate, ideate, build, and streamline major signal repository to enable ML and unique insights.
• Analyze data, partner with other Business Data Scientists, to help us understand drivers of historical business performance.
• Leverage insights to determine areas of opportunity for improvement in business treatment.
• Build causal ML models to improve business channel assignments and treatment.

Benefits

• Bonus
• Equity
• Health benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Web Search Portals, Libraries, Archives, and Other Information Services
• Education Level: Master's degree