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Job Details
Posted date: Mar 24, 2025
Location: Seattle, WA
Level: Senior
Estimated salary: $171,500
Range: $141,000 - $202,000
Description
Design and implement robust data pipelines to collect, process, and transform complex and large data sets from various data sources.Develop various types of machine learning models, conducting model evaluation, and collaborating with engineering teams to deploy the models into a production environment.
Develop and apply Natural Language Processing (NLP) models (such as sentiment analysis, topic modeling, etc.) to extract insights from unstructured text data.
Collaborate with cross-functional teams within POps and HR Engineering organizations to understand the business problem, define project scope, gather the requirements, and develop ML solutions that address the problem effectively.
Communicate technical concepts and findings to both technical and non-technical audiences, enabling POps stakeholders to make informed decisions about Googlers.
We are a data science team that use AI/ML to enable Google’s people analytics strategy. We build AI solutions that empower people analysts and leaders to make data-driven decisions, and inspire People Analytics to be on the cutting-edge. We achieve this through a culture of continuous learning, sharing, and growth.
This is a unique opportunity at Google to be at the forefront of applying AI/ML to solve complex people-analytics challenges at a global scale. In this role, you'll leverage Google's people data and cutting-edge technology to develop and deploy innovative solutions that directly impact Googlers' lives. You'll also play a crucial role in shaping the future of people analytics by collaborating with cross-functional teams, upskilling colleagues in AI/ML, and fostering a data-driven culture within people operations. This role offers the chance to make a real difference in the lives of Googlers while contributing to the advancement of AI/ML in the HR domain.
The US base salary range for this full-time position is $141,000-$202,000 + 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.
Qualifications
Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience with data science tech stack (e.g., Python) and database languages (e.g. SQL).
Preferred qualifications: PhD degree in Computer Science, Statistics, or other relevant quantitative disciplines, or an equivalent amount of machine learning experience.
Familiarity with reporting solutions, and visualization/dashboarding tools. Proven ability to translate ambiguous business needs into clear technical requirements for impactful data products.
Ability to take initiative with excellent leadership and communication skills.
Comfortable with engineering best practices, including developing BRDs/PRDs/Design Docs, code reviews, etc., ensuring analytical accuracy.
Extended Qualifications
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience with data science tech stack (e.g., Python) and database languages (e.g. SQL).
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