Data Science Leader, CX

Socket.dev; Palo Alto (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

SAP is seeking a leader in Data and Applied Science to build the semantic and contextual foundation for SAP's AI agents. You will guide high-impact AI programs, mentor data scientists and engineers, and partner with executives to align AI investments with business objectives.

As part of the Data and Applied Science team, you will shape enterprise AI platforms, governance, and reusable services while delivering measurable business value across multiple product areas.

Qualifications

• 10+ years leading AI teams and driving complex AI initiatives.
• Define technical strategy and align AI investments with business goals.
• Proven culture of technical excellence and continuous learning.
• Excellent stakeholder management and executive communication.
• 5+ years people management leading data science/AI teams.
• Experience delivering large-scale AI programs with executives.

Skills

People leadership

Technical strategy

Technical excellence

Stakeholder management

People management

Program delivery

Global leadership

AI adoption & governance

Thought leadership

Domain knowledge

SAP stack experience

Job description

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

The context engine that makes AIenterprise ready.

Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As part of our Data and Applied Science team, you'll build the context enginegrounded in SAP’s Business ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.

What you'll build:

The Data and Applied Science team will build the semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. Your team will build and scale the layer that makes that possible.

What you'll bring:

Requirements for this position include the following:

Leadership & Strategic Skills

• 10+ years proven experience leading, mentoring, and growing high-performing teams of data scientists, machine learning engineers, and AI practitioners, with a strong track record of driving complex AI initiatives from concept to production across multiple teams and stakeholders.
• Ability to define technical strategy, establish team priorities, and align AI investments with business objectives, product roadmaps, and customer outcomes.
• Experience building a culture of technical excellence, operational rigor, and continuous learning.
• Excellent stakeholder management and executive communication skills, with the ability to influence senior leadership and translate technical concepts into business value.
• 5+ years of people management experience leading data science and AI teams, with demonstrated success hiring, coaching, and retaining top AI talent.
• Proven experience delivering large-scale AI programs across multiple teams and businessunits andpartnering with senior executives to define AI strategy and investment priorities.

Desirable Skills

• Experience leading globally distributed teams and cross-organizational AI initiatives, including managing budgets, hiring plans, vendor relationships, and strategic partnerships.
• Experience defining AI adoption strategies, measuring business impact through KPIs, and establishing reusable enterprise AI platforms, governance frameworks, and shared services across multiple product areas.
• Thought leadership demonstrated through patents, publications, conference presentations, open-source contributions, or industry recognition in AI, knowledge graphs, semantic technologies, or enterprise intelligence.
• Knowledge of SAP’s domains, data models, metadata structures and core business processes end-to-end.
• Experience with the SAP data and AI platform stack SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub.

Key Knowledge and Abilities: