Connected TV Data Scientist

2 Months ago • 3-5 Years • Data Analyst • $127,000 PA - $187,000 PA

Job Summary

Job Description

This role involves partnering with Product Managers, Engineers, and UXR leaders on CTV's search and discovery teams to enhance content recommendations and drive user/watchtime growth. The Data Scientist will work with technical teams building recommendation systems across various CTV surfaces and applications (e.g., YT Living Room Apps). Responsibilities include collaborating on cross-functional projects, defining and improving success metrics, gathering and analyzing data, and designing and evaluating mathematical models to solve business problems. The ideal candidate will have experience with analytics, coding (Python, R, SQL), and querying databases. They will be responsible for improving the user experience and diversifying viewer interests.
Must have:
  • Master's degree in related quantitative field or equivalent experience
  • 3+ years experience using analytics to solve business problems
  • Proficiency in Python, R, SQL
  • Experience querying databases and statistical analysis
  • Collaborate with stakeholders to identify business questions
  • Gather, extract, compile data across sources
Good to have:
  • 5+ years of relevant work experience
  • PhD degree
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

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

Preferred qualifications:

  • 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 a PhD degree.

About the job

In this role, with the support of a technical lead, you will partner with Product Managers, Engineers and UXR leaders on CTV’s search and discovery teams to unlock Connected TV (CTV) user/watchtime growth with improved content recommendations that serve our viewer’s needs while also diversifying their interests. You will work with technical teams building recommendation systems across CTV surfaces (e.g., home, search, watch next) and applications (e.g., YT Living Room Apps).

The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 .

Responsibilities

  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  • Analyze Living Room discovery (recommendation models). Define and improve success metrics that are proxies of good user experiences.

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