Google

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

Preferred qualifications:

• Master's degree or PhD in Data Science, Computer Science or a related quantitative field.
• 7 years of experience as a data scientist applying advanced statistical and machine learning methods on real-world problems.
• Experience in Generative AI, defining, building and evaluating AI-agents and leveraging foundational language models for introducing advanced new capabilities within existing products and systems.
• Experience with relevant libraries and frameworks (e.g., TensorFlow, LangChain, PyTorch, etc.).
• Experienced in building and managing large-scale data processing pipelines (e.g., BigQuery).
• Experience in Cloud Computing, Machine Learning Operations and in Google Cloud Platform (GCP)/Vertex-AI.

About the Job

Our Data Science team leads data-driven decisions across Waze's core functional areas, including the Waze Map and Map Editor, Advanced Guidance and Voices, Growth and Strategy, User Communications and more. The team members are embedded within the Waze development Squads. We define data requirements and analytics strategies, execute experiments, deliver in-depth analyses and provide actionable recommendations. The team’s contribution is crucial for the effective development and safe landing of the new Waze features and help guiding the overall product strategy.

We are responsible for the research and development of advanced experimentation and Causal Analysis infrastructures to measure, understand and attribute features’ impact. We also own a comprehensive Data Warehouse, providing essential dashboards and analytics tools, including Gen-AI agents, to empower both Data Scientists and stakeholders throughout the organization.

Responsibilities

• Develop and implement Measurement Methodologies and Evaluation Frameworks. Assess the performance, accuracy and groundedness of AI Agents, including the automated generation of synthetic training and evaluation data.
• Work with various teams including software developers, data engineers and product managers, to define the requirements and implement Gen-AI models and solutions to drive innovation.
• Translate complex technical concepts and investigative findings into clear, actionable insights for both technical and non-technical stakeholders.
• Lead the design, development and deployment of Generative AI Agents for conversational driving-related experiences and scaling the ingestion, annotation and utilization of user generated contect and geospatial data feeds.