Business Data Scientist, Ads Revenue

Google•Mountain View, CA

8d•$141,000 - $202,000

About The Position

Google's leadership team hand-picks thorny business challenges, and members of BizOps 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. Our team is behind the GBO Finance organization. We bring an aligned perspective from across regions and functions that helps to shape the strategic direction for the Global Business Organisation. We also own core business finance operations for GBO and are always seeking opportunities to standardize, automate and find scale so that we can have the most impact for the Ads business. This role is within the business pillar of the GBO Central Finance team. Broadly, this team is responsible for business forecast and goal setting for the Ads business, along with managing key business-related processes. The Business Operations and Strategy team at Google plays a critical role in defining and driving strategic, operational and organizational improvements across the company. Also known as "BizOps", the group operates like an internal consulting group working on a range of critical projects and issues. BizOps creates strategies for promoting growth of our products like YouTube, Chrome and Mobile. They handle issues around partner development, strategy work in emerging markets such as Africa and India, as well as pricing strategies across our B2B and consumer products. The BizOps team is at the forefront of Google's fast-moving strategic priorities, addressing operational challenges and enabling innovation.

Requirements

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.

Nice To Haves

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 with financial and statistical modeling, with a proven track record of applying AI/ML frameworks to solve complex forecasting, resource allocation, and project viability challenges.
Experience with SQL to create data architecture, along with using Python or R for building automated data products.
Experience with optimization libraries and version control best practices.
Strong communication skills, enabling partnership with executive leadership to drive business judgment and influence organizational strategy.

Responsibilities

Use AI/ML to solve business problems at scale. Familiar with advanced models in forecasting and optimization.
Focus on forecasting, financial modeling, building and maintaining models to assess project viability and expected returns, and guiding resource allocation.
Build scalable solutions to optimize financial processes. Analyze workflows, pinpoint bottlenecks, and develop statistical models to enhance the efficiency of existing processes while minimizing manual effort. Leverage technology and automation to improve productivity and reduce the risk of errors.
Develop data solutions that provide clear insights, enabling users to make informed decisions and work more efficiently. Analyze financial results and performance metrics to inform decision-making at both operational and strategic levels.
Implement best practices for reporting, dashboards, and data visualization to effectively communicate financial information.