Senior Staff Data Scientist Manager, Research
Job Summary
Job Description
- Master's degree in quantitative field
- 8+ years analytics experience (10 years without PhD)
- 2+ years team management experience
- Proficiency in Python, R, SQL
- Data modeling & evaluation skills
- PhD degree
- 10+ years analytics experience
- 6+ years people management in technical leadership
- 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.
- 10 years of 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.
- 2 years of experience managing a team of analysts, data scientists, or product analysts.
Preferred qualifications:
- 12 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.
- 6 years of experience as a people manager within a technical leadership role.
About the job
NetSoft's mission is to enable agile planning, optimized design, and rapid deployment cycle times for Google production networks.
The team works on a varied set of business-critical software systems ranging from developing Network Risk assessments, Failure modeling and Network-Demand generation systems. In particular, the areas of Risk and Forecasting both require experienced scientists with deep industry experience, who can provide thought-leadership and strategic thinking.
Network Risk measurement is specially an area that is filled with deep problems that are critical for measuring and baselining the product requirements both from internal and external perspective.
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 knowledge. Design and evaluate models to mathematically express and solve defined 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, 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.
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About The Company
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.
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