Description

Minimum qualifications:

• 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.
• Experience with natural language processing and other machine learning modeling concepts.
• Experience with experimentation methodology including causal inference, hypothesis testing, and statistical validity.

Preferred qualifications:

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

About the job
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, within Go-to-Market (GTM), serves as the strategic intelligence partner for product teams, transforming massive volumes of unstructured conversational data into quantified, trusted insights that bridge the gap between customer feedback and product decisions. This is a high-visibility initiative critical for accelerating the Ads product adoption flywheel and shaping GTM strategy for priority products.

In this role, you will be the vital link connecting the customer to bottom-line business metrics and overarching product strategy. Working directly with the structured signals and thematic data generated by our NLP pipelines, you will apply causal inference and incrementality testing to determine the true business impact of customer conversations. Your analyses will connect specific customer friction points to outcomes like product adoption, business, and possession. By providing statistical evidence of how customer feedback drives user behavior, you will directly shape and prioritize our product roadmaps and GTM initiatives.

The US base salary range for this full-time position is $163,000-$237,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Design and execute causal inference studies to measure the impact of product changes or interventions.
• Partner with product teams to design robust A/B tests and quasi-experiments that validate the hypotheses generated by our NLP insights.
• Connect the structured data outputs from our NLP models with core business metrics to size the business opportunity of addressing specific customer feedback.
• Perform exploratory data analysis to support emerging GTM questions.

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Requisition #: 124561657387983558

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