What are the responsibilities and job description for the Business Data Scientist, YouTube Music Partners position at YouTube?
Minimum 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, 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
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 team you will work closely with Partnership teams to shape the future of YouTube Music economics. You will need to leverage techniques from causal inference, advanced statistical modeling, and machine learning. It will be your responsibility to determine the best approach for solving problems, and to 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. 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 wearing multiple hats, is passionate about conducting causal studies and helping stakeholders implement data driven decisions. You will require 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. 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 A/B experiments and 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.
