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As a Business Data Scientist in YouTube Business Go-To-Market (GTM) Impact Measurement team you will work with business leaders to help shape the future of YouTube. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Requirements

• Experience in causal inference, A/B testing, statistical modeling, or Machine Learning.
• Experience in programming with SQL and Python, and in leveraging ML or statistical libraries (e.g. TensorFlow, Scikit-learn, XGBoost, Keras, Pandas).
• Experience in causal inference, Bayesian statistics, and ML.
• Experience in Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, and R.
• Experience drawing conclusions from data, breaking down technical concepts into simple terms, connecting with, and presenting to, technical and non-technical stakeholders, and recommending actions.
• Publications related to Data Science, posters or presentations in AI/ML conferences, or patents.

Responsibilities

• Design and execute causal studies to address critical business questions.
• Leverage advanced statistical models to find business insights in experimental and observational data.
• Serve as a peer reviewer and consultant for causal studies across the organization.
• Leverage rigorous techniques from causal inference, advanced statistical modeling, and Machine Learning (ML).
• Use a large set of tools from experimental to observational techniques, touching on a broad range of problems from different functional and product areas.
• Keep up with advances in the causal inference literature.
• Develop new methods in collaboration with your teammates and work with the summer interns on research projects.

Other

• Present and communicate actionable insights and recommendations to executives and cross-functional partners.
• Determine the best approach for solving problems, and communicate clearly with decision-makers who may or may not have a strong technical background.
• Be comfortable in taking on various roles, and be passionate about conducting causal studies and helping stakeholders implement data driven decisions.
• Creative problem-solving and stakeholder management skills are critical.
• Attend relevant conferences and organize internal events to keep the toolkit updated and to educate the broader Google community.