Senior Business Data Scientist, Agentic AI, Finance

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.

As a Senior Business Data Scientist, you will collaborate with other data scientists, analysts, engineers, and Product Managers (PMs) to create end-to-end AI/ML and Agentic solutions to transform Finance processes and drive AI adoption across the organization. You will demonstrate experience in solving business problems through a product/transformation mindset with AI/ML technical knowledge.

Responsibilities

• Work cross-functionally with analysts, engineers, and program managers to develop and deploy agentic and AI solutions.
• Use a product-driven mindset to transform key Finance processes using Agents and AI.
  
• Partner with your product team to solve problem and deliver end-to-end process transformation.
• Operationalize and monitor solutions; design and deploy model endpoints that adhere to high-availability Service Level Agreements (SLAs), implementing necessary health checks, retries, and fallback mechanisms.
• Communicate results to peers, stakeholders, and leaders.

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 building agentic workflows (e.g., agent development kit (ADK), context management, and prompt engineering) to transform corporate processes.

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.