Business Data Scientist, Impact Measurement
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Minimum qualifications:
- Master's degree in a STEM field or equivalent practical experience.
- 3 years of industry or PhD Data Science experience.
- 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).
Preferred qualifications:
- PhD in a STEM field.
- Experience in a Data Science role supporting Sales, Marketing, or Customer Support.
- 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.
About the job
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. You will have to leverage rigorous techniques from causal inference, advanced statistical modeling, and Machine Learning (ML). It will be your responsibility to determine the best approach for solving problems, and communicate clearly with decision-makers who may or may not have a strong technical background.
You will be a detail-oriented problem-solver with broad knowledge of causal inference, Bayesian statistics, and ML. You will use a large set of tools from experimental to observational techniques, touching on a broad range of problems from different functional and product areas. You will 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.
Effective data scientists on this team keep up with advances in the causal inference literature. When available methodologies are not well suited for the problem you are trying to solve, you will be encouraged to develop new methods in collaboration with your teammates and work with the summer interns on research projects. You will also attend relevant conferences and organize internal events to keep the toolkit updated and to educate the broader Google community.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. 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.
The US base salary range for this full-time position is $141,000-$202,000 + 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 studies to address critical business questions.
- Leverage advanced statistical models to find business insights in experimental and observational data.
- Present and communicate actionable insights and recommendations to executives and cross-functional partners.
- Serve as a peer reviewer and consultant for causal studies across the organization.
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