Location: Kirkland, WA
Cap-Exempt H-1B Position — No lottery required
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: - Health, dental, vision, life, disability insurance - Retirement Benefits: 401(k) with company match - Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment - Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance - Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks - Baby Bonding Leave: 18 weeks - Holidays: 13 paid days per year **Minimum qualifications:** - Master's degree in a quantitative field (Statistics, Mathematics, Data Science, Bioinformatics, Economics, etc.) or equivalent practical experience - 3 years of experience in a data science field. - Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL). - Experience using analytics to solve product or business problems, querying databases or statistical analysis. **Preferred qualifications:** - PhD in Statistics or related quantitative discipline. - 2 years of experience, including statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods. - Experience in controlled experiment design and causal inference methods. - Ability to prioritize requests and partner well in an environment with competing demands from stakeholders. - Ability to convince business stakeholders and communicate analysis insights to non-technical audiences and willingness to both teach others and learn new techniques. - Excellent communication and team-work including problem-solving skills. **About The Job** Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection,