Data Science Manager I, AI/ML

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, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

Responsibilities:
Hire, manage, and coach a Data Science pod based in India. Build community, promote a welcoming environment, and develop a performing team of data scientists.
Provide technical expertise and knowledge of Machine Learning, Agent development lifecycle, statistical analysis, applied mathematics, and data science applications to review solution design, Python code, and guide technical architecture.
Translate business questions into analysis, define data requirements, and develop project roadmaps for open-ended problems.
Oversee development, deployment, and integration of Artificial Intelligence/Machine Learning (AI/ML) models, such as predictive models, Natural Language Processing (NLP) models, AI solutions and adverse impact analysis.
Utilize executive communication to persuade executive leaders, align partner teams with engaging goals, and integrate workstreams across multiple People Operations initiatives.

Minimum qualifications:
Master's degree in a Statistics, Engineering, Sciences, or a related quantitative field, or equivalent practical experience.
7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
3 years of experience in people management within a technical leadership role.
Experience with building and deploying machine learning models for business applications.

Preferred qualifications:
PhD in Computer Science, Statistics, Engineering, or a related quantitative field, or equivalent practical experience.
9 years of experience with using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with leading, developing, and prioritizing work for an offshore pod across timezone.
Experience in collaborating with executive leaders and driving cross-functional alignment, with excellent stakeholder management skills.
Excellent technical and applied ML skills, with the ability to drive technical designs.