Business Data Scientist, AI Analytics

About the position

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.

Responsibilities

• 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.

Requirements

• 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).

Nice-to-haves

• 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.

Benefits

• 401k
• health_insurance
• dental_insurance
• vision_insurance
• life_insurance
• disability_insurance
• paid_holidays
• paid_volunteer_time
• tuition_reimbursement
• professional_development
• employee_stock_purchase_plan
• flexible_scheduling
• gym_membership
• mental_health_days
• wellness_programs