Data Science Leader, CX

Socket.dev

Bellevue (WA)

Hybrid

USD 283,000 - 609,000

Full time

3 days ago

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Benefits offered by this job

Health benefits

Remote work options

Job summary

SAP is seeking an AI leader to shape the semantic and contextual foundation for enterprise AI. You will drive architecture, governance, and platform strategy across large, cross-functional teams while delivering scalable AI solutions grounded in SAP's data models and business processes.

This role emphasizes mentorship, executive collaboration, and delivering measurable business value through advanced AI, ML, and knowledge-graph driven approaches.

Qualifications

10+ years leading data science teams and AI programs.
5+ years people management, hiring AI talent.
Experience delivering enterprise-scale AI initiatives across teams.
Ability to translate technical concepts into business value.
Strong stakeholder management and executive communication.

Responsibilities

Define AI strategy, governance, and platform roadmap for enterprise-scale deployments.
Lead multi-team AI initiatives and collaborations with senior executives.
Architect AI solutions integrating knowledge graphs and semantic layers.
Ensure responsible AI practices and robust model lifecycle governance.

Skills

Leadership

AI strategy

Machine learning

Knowledge graphs

Ontology engineering

Semantic technologies

MLOps

LLM Ops

Stakeholder mgmt

Enterprise AI

Tools

None

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:

AI Platform, Architecture & Governance

Experience defining AI/ML architecture, platform strategy, model governance, responsible AI practices, and operational frameworks for enterprise-scale deployments.
Ability to evaluate emerging AI technologies and establish best practices for ML Ops, LLM Ops, and model lifecycle management‑making pragmatic build‑versus‑buy decisions across platform investments and technology roadmaps.

Knowledge Graphs, Ontologies & Enterprise Intelligence

Strong domain expertise in ontology engineering, semantic technologies, metadata management, entity resolution, taxonomies, and knowledge representation, with demonstrated experience designing, building, and scaling ontology-driven enterprise intelligence solutions, including knowledge graphs, semantic layers, and business knowledge models.

Experience integrating knowledge graphs and ontology layers with machine learning, generative AI, agentic AI, RAG architectures, and enterprise data platforms to improve reasoning, explainability, grounding, and business context.

Ability to collaborate with domain experts and business stakeholders to translate complex business processes, data assets, and enterprise knowledge into reusable semantic and knowledge graph frameworks.

Deep knowledge of SAP application data models, domain processes, and enterprise data architecture, with the ability to apply this understanding to design ontologies, semantic layers, and knowledge graph solutions that accurately reflect SAP's business and application context.

Dataand Applied Science– General Job Profile Skills

Model Training

Ability to conduct Machine Learning Model Training. Employees who excel in this skill have expertise in statistics, computer science, and mathematics, as well as proficiency in software tools and programming languages. They are capable of selecting the right algorithm for a problem, preparing data sets, and testing model accuracy.

Deep Learning

Ability to utilize deep learning and neural networks to enable machines to learn from data and make decisions. Employees who excel in this skill have specialized abilities in mathematics, programming, and data analysis, making them highly coveted in the tech industry.

Data Engineering

Ability to design, build, and maintain infrastructure for data collection, transformation, storage, and analysis. Employees who excel in this skill have a high level of technical expertise in programming, data modeling, and data visualization.

Agentic Orchestration

Ability to design, delegate, and supervise multi-agent workflows involving autonomous AI agents with multi-step reasoning and coordination. Employees who excel in this skill manage task decomposition, agent communication, error handling, quality human validation, and design agent harnesses for long-running tasks, context durability, tool lifecycle, and sub-agent coordination.

Semantic Retrieval

Ability to design, implement, and optimize semantic search and retrieval architectures including RAG pipelines, knowledge graphs, and hybrid vector/keyword search systems and Lakehouse architectures. Employees who excel in this skill have deep expertise in embedding models, retrieval optimization techniques, and modern data architecture patterns.

Where you belong:

Join a collaborative, forward-thinking team defining how enterprise AI actuallyworks on aglobal scale. You'll work alongside curious engineers, thoughtful product minds, and applied researchers all focused on building AI that customers can trust in the highest-stakes business processes. There's room to grow into new technical spaces, ship real impact, and shape SAP's AI future. If you value learning, real ownership, and building foundational infrastructure that matters, you'll feel at home here.

#dlhiring

Bring out your best

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

We win with inclusion

SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

Compensation Range Transparency

SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step towards demonstrating SAP’s commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted annual combined range for this position is 282500-609200(USD). The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.

We are ethical and compliant

Our leadership credo: Do what’s right. Make SAP better for generations to come. We believe that great leadership extends far beyond the mere pursuit of business goals. We value and foster leadership that is driven with purpose and integrity. Our leaders are role models who uphold SAP’s values and shape SAP’s culture of integrity, by demonstrating and championing ethical and compliant behavior towards all stakeholders.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.

Nearest Major Market: Seattle

Nearest Secondary Market: Bellevue

Job Segment: Testing, Cloud, Data Architect, Open Source, ERP, Technology, Data

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