About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
About the role
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.
What they're looking for
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience
- 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis
- Experience architecting scalable enterprise AI solutions and generative AI pipelines (e.g., Large Language Models (LLMs), LangChain, Vertex AI, or autonomous agents
More about this role
- Build developer frameworks to accelerate and improve the Business Intelligence (BI) development lifecycle and solutions.
- Help design and build highly reusable, complex skills, agents, and procedures at the AI Platform level that can be leveraged across multiple projects and by both technical developers and non-technical finance stakeholders.
- Act as a strategic zeroth finance customer for Deepmind technology, partnering with core engineering teams on early-stage design, usability, and architecture to ensure new features are optimized for complex, real-world deployment scenarios.
- Act as connective tissue between Finance AI developer, CorpEng, Deepmind and Cloud to define Finance technical requirements, aligning cross-organizational roadmaps, resolving ambiguity, and shipping outcomes that serve both internal and external customers.
- Develop scalable, maintainable internal and external software-as-a-service (SaaS) products decoupled from internal dependencies.
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, coding (e.g.,...
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