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Where is the work:
Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.
About the role
As Data Scientist Manager, you will report to the AI in Engineering team leader, and lead a team of exceptional data scientists and software engineers to deliver bleeding edge internal products to enhance engineering design. You will be responsible for delivery, technical standards, governance, and cross-functional execution required to build and operate engineering intelligence platforms.
This is a player-coach leadership role. You will develop a high-performing multidisciplinary team while remaining technically engaged in architecture, reviews, delivery, and critical problem solving. You will work across engineering, IT, cybersecurity, legal, and other partner organizations to ensure that the team delivers secure, reliable, high-quality capabilities.
What you will do
Lead delivery of engineering intelligence platforms and shared technical capabilities.
Manage, coach, develop, and retain a multidisciplinary technical team.
Establish architecture and engineering standards across components and use cases.
Own governance, quality, operational accountability, and delivery discipline within the team.
Coordinate with engineering, IT, cybersecurity, legal, and other partner organizations.
Lead hiring, team formation, capability development, and succession planning.
Provide technical direction for AI/ML, software, data, cloud, and platform work.
Support production deployment, reliability, security, and operational readiness.
Guide to the use of spec-driven development, AI-assisted software engineering, and advanced code assistants.
Manage distributed and international collaboration, including India-based engineering roles.
Contribute hands-on to architecture, technical reviews, and critical delivery work.
Required qualifications
Master’s degree or PhD in a relevant technical field.
Twelve or more years of relevant experience, including management experience.
Experience managing data science, AI/ML, software engineering, or multidisciplinary technical teams.
Experience leading production AI/ML or engineering technology programs.
Experience with technical architecture and engineering standards.
Experience with GCP and cloud-based platforms.
Experience hiring, coaching, and developing technical talent.
Experience with governance, quality, security, and operational accountability.
Experience coordinating with engineering, IT, cybersecurity, legal, and other cross-functional partners.
Strong software engineering or data science background.
Experience with spec-driven development and AI-assisted software engineering.
Experience managing distributed or international teams.
What success looks like
You establish a high-performing team operating model and delivery rhythm.
The team delivers production-ready capabilities for multiple engineering use cases.
Consistent architecture, quality, governance, and operational standards are adopted.
Reliable GitHub integration and testing workflows are established.
Team capability improves through hiring, coaching, mentoring, and standards.
Cross-functional operating relationships with engineering, IT, cybersecurity, and legal are effective and…