Staff Data Scientist, Research, Real World Journeys
Job Summary
Job Description
- Master's degree in related quantitative field
- 8 years experience (or 6 with PhD) using analytics
- 4 years experience in predictive modeling
- LLM application experience
- Proficient in Python, R, SQL
- 10 years experience (or 8 with PhD)
- Experience solving unstructured business problems
- Exceptional leadership skills
- Bonus
- Equity
- Benefits
8 skills required
Job Details
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
- 4 years of experience in predictive modeling.
- Experience applying large language models to help solve problems.
Preferred qualifications:
- 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
- Track record of solving unstructured business problems with data science and translating results into impactful business/product recommendations.
- Ability to think critically, analyze complex problems, and develop data-driven solutions.
- Excellent verbal and written communication skills with the ability to articulate complex concepts to both technical and non-technical stakeholders.
- Exceptional leadership skills with the ability to inspire other data science team members.
About the job
The Real World Journeys Data Science team is part of the broader Search Data Science and Engineering team. We focus on enhancing user experience and driving growth across a wide range of commercial search verticals, including Lodging, Flights, Events, Things to Do, Food and Drink, Services, and more. We work closely with the Product and Engineering teams to shape strategy and ensure data-driven decision-making throughout the organization.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
The US base salary range for this full-time position is $197,000-$291,000 + 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 .
Responsibilities
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics or mathematical models.
- Use custom data infrastructure or existing data models as appropriate, using specialized grip. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Apply analytics, experimentation, causal inference and Large Language Model (LLM) to address business challenges.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure or validate data to ensure quality and review the dataset to ensure it is ready for analysis.
- Frame and solve ambiguous business problems while researching and developing new methodologies to solve them when needed.
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