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Google Inc.

Business Data Scientist, YouTube Music Partners Job at Google Inc. in New York

Google Inc., New York, NY, United States, 10261

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About the job

The YouTube BizOrg (Business Organization) Music and Media Team helps shape the future of YouTube by working closely with its business leaders to steer relationships with partners. Our mission is to empower Music and Media partners and users to grow together on YouTube. We are a full-stack analytics team offering data engineering, business intelligence, and data science capabilities serving as collaborative thought partners with business leaders to ensure decisions are data-informed.

As a Business Data Scientist in YouTube BizOrg Music and Media, you will work closely with Partnership teams to shape the future of YouTube Music economics. You will leverage techniques from causal inference, advanced statistical modeling, and machine learning. You will determine the best approach for solving problems and communicate clearly with decision-makers who may or may not have an excellent technical background. You will be a detail-oriented problem-solver with broad knowledge of causal inference, Bayesian statistics, and machine learning, using a range of tools from experimental to observational techniques across functional and product areas. You will wear multiple hats, be passionate about conducting causal studies, and help stakeholders implement data-driven decisions while applying creative problem-solving and stakeholder management skills.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Salary ranges are determined by role, level, and location. Individual pay is determined by work location and other factors, including job-related skills, experience, and education. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that compensation details listed reflect the base salary only and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

  • Design and execute A/B experiments and causal studies to address critical business questions.
  • Leverage advanced statistical models to derive business insights from 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.

Qualifications

  • Master's degree in a Science, Technology, Engineering, or Mathematics field or equivalent practical experience.
  • 3 years of experience in Data Science.
  • 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 Science, Technology, Engineering, or Mathematics 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, communicating with both technical and non-technical stakeholders, and recommending actions.
  • Publications related to Data Science, posters or presentations in AI/ML conferences, or patents.

Equal opportunity

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, and to providing equal employment opportunities regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

Google is a global company and, to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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