Business Data Scientist, Global Business Strategy and Operations

Google•Mountain View, CA

2d•$138,000 - $198,000

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. Global Business Strategy and Operations (GBS&O) is part of the Go-to-Market organization making sure Google's business pursues the best strategy and executes flawlessly. GBS&O architects the future of Google’s global ads business, consisting of highly pragmatic and results-oriented investigative and experts in business operations. The Data, Insights, and Analytics (DIA) team partners with GBS&O team members to drive the best decisions possible with data. We build creative ML and Data Science solutions to drive strategy and business impact. We help our organization make decisions to ensure the Ads Business continues to thrive. In this role, you will help GBS&O partners make decisions using data owning the full data science lifecycle for high-impact, ambiguous business problems, from initial analysis to strategic recommendation. You will drive alignment and simplicity to manage a range of high-impact projects (e.g., causal inference, predictive modeling) initially focusing on projects, including seller incentives design and impact analysis, working closely with Strategy and Finance partners. You will own the technical infrastructure and investigative roadmap for systems and methodologies that measure effectiveness of our incentives programs to drive the executive-level roadmap requiring flexibility to pivot based on evolving business needs.

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 in designing and implementing causal inference methods.
Experience building and maintaining BI infrastructure, dashboards, and data pipelines.
Proficiency in database querying (SQL).
Excellent communication, presentation, and stakeholder management skills, with the ability to explain concepts to audiences.

Responsibilities

Lead the analytics, data infrastructure, and measurement methodology of seller incentives, designing data pipelines and tooling to executing advanced statistical analysis and generating insights.
Partner with Strategy and Operations and Finance stakeholders, who own the end-to-end processes for incentives design, to translate high-priority business problems into clear, data-driven strategies and decisions.
Own the full data science lifecycle, using your causal inference, predictive modeling, and descriptive analytics expertise to build frameworks that solve business problems.
Manage ambiguous problems working with datasets, using SQL, R, and Python to find creative, scalable solutions and build automated data pipelines, BI infrastructure, and dashboards from the ground up.
Act as a data storyteller and partner, translating findings into compelling narratives and recommendations that influence and align executive leaders and teams (Strategy, Product, Engineering).