Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- 2 years of experience managing projects and defining project scope, goals, and deliverables.
Preferred qualifications:
- Master's degree in a quantitative discipline.
- 4 years of industry experience analyzing, extracting, and visualizing insights from datasets.
- 2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
- 2 years of experience with machine learning systems.
- Experience building data science and machine learning solutions (e.g. sizing business problems, data exploration, feature engineering, modeling).
- Excellent communication skills, including the ability to convey the results of the work.
At Google we work to earn our users’ trust every day. GCP Protection Analytics (GPA) is part of Google Cloud’s organization of abuse and security experts working daily to make Cloud a safer place. We are a machine learning, data science, and analytics team that partners with product and engineering teams across Cloud to deliver data science solutions to stop bad actors while also enabling a trusted experience for our customers.
As a member of the Google Cloud Platform (GCP) Protection Analytics team, you will use the machine learning and business problem-solving skills to create solutions that address key abuse and security risks while also empowering our customers to grow their businesses on Google Cloud. You will manage everything from identifying new business problems we need to build data science solutions to solve, to model building, to building partnerships with other Cloud teams to ensure we can deliver solutions. You will design, implement, and improve machine learning solutions in production.The US base salary range for this full-time position is $126,000-$181,000 + 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.
- Deliver cross-functional data science and analytics projects, including executing data analysis with SQL and Python, collaborating with product and engineering partner teams, and managing the project timelines.
- Develop an understanding of the abuse, security, and customer experience business problems our team works on in order to lead the ideation, design, and development of data science and analytics solutions to solve them.
- Perform data analysis to drive decision-making for our team, such as monitoring the rollout of new models, analyzing the impact of rules-based or machine learning model changes, or investigating the root cause of changes in key metrics.
- Communicate with technical and non-technical audiences at various levels of seniority, including producing write-ups, dashboards, and data visualizations to convey the findings and recommendations to our team and cross-functional stakeholders.
