Senior Data and Applied Scientist, HCM Autonomous Suite, Palo Alto

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Senior Data and Applied Scientist, HCM Autonomous Suite, Palo Alto

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 a Data and Applied Scientist at SAP, you'll build the context engine grounded in SAP’s Business ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.

Whatyou'llbuild

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. You'll build and scale the layer that makes that possible.

Design and maintain enterprise ontologies and semantic modelsthat give AI agents accurate, grounded understanding of SAP and connected business landscapes harmonizing data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers into unified semantic layers.

Build AI capabilitiesincluding RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production.

Develop AI capabilitiesincluding generative AI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets.

Leverage SAP's deep data and process contextincluding SAP data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to ground AI solutions in real enterprise reality.

Work with cloud and data platformsincluding Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP to support reliable, scalable AI workflows.

Partner across product, engineering, business, and customer-facing teamsto translate ambiguous business challenges into concrete AI solutions from concept through deployment and continuous improvement.

Apply machine learning, deep learning, and statistical modelingto develop and evaluate AI solutions using real-world enterprise datasets.

Whatyou'llbring

5+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.

Master's or PhDin Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field

Hands-on experience designing enterprise ontologies and semantic models; proficiency in at least one graph query language (SPARQL, Cypher, or GQL); understanding of trade-offs between RDF triple stores and property graph databases.

Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.

Strong Python and SQL skillswith production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.

Proven track record deploying and operating AI/ML solutionsin production including handoff, lifecycle support, and continuous improvement.

Experience with big data infrastructure and cloud environmentsDatabricks or equivalent, plus at least one major cloud (AWS, Azure, or GCP).

Excellent communication and stakeholder management skills, with the ability to work cross-functionally in agile environments.

Preferred Qualifications

Deep working knowledge of SAP data models, metadata structures, and core business processes end-to-end.(SAP knowledge is a strong accelerator)

Hands-on 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.

Deep expertise across the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) and/or property graph query languages (Cypher, GQL).

Deep expertise in machine learning and deep learning, with experience developing, evaluating, and improving models on real-world datasets.

Experience with agentic AI, reasoning frameworks, planning, orchestration, tool use, or multi-agent architectures.

Experience contributing to reusable AI platforms, foundation model initiatives, or shared AI services adopted across multiple product areas.

Ability to design upper-level and mid-level ontologies aligned with industry standards and apply semantic interoperability frameworks across complex application landscapes.

Understanding of HR/HCM domain semantics and the ability to translate SuccessFactors business concepts, processes, and terminology into semantic models, knowledge representations, AI grounding, and agentic experiences.

Experience working with SAP SuccessFactors extensibility and integration technologies, including OData APIs, Integration Center, SAP BTP, and/or other SAP integration patterns.

Experience applying analytics, machine learning, or statistical methods to workforce use cases such as attrition, headcount, workforce planning, skills, compensation, recruiting, performance, engagement, or talent intelligence.

#LI-MM10

Whereyoubelong

Join SAP SuccessFactors at a pivotal point in the evolution of enterprise AI, where we are moving beyond traditional applications and analytics toward intelligent, autonomous agents that can understand HCM context, reason over trusted business data, and help customers make better workforce decisions. As part of the SuccessFactors Line-of-Business, you will work at the intersection of HCM domain expertise, enterprise data, applied AI, and agentic technologies - helping shape how employees, managers, HR leaders, and businesses interact with SAP through intelligent experiences. You will collaborate with product, engineering, data, and research teams to ground autonomous agents in SuccessFactors business processes, semantics, policies, and data, while building solutions that are accurate, responsible, secure, and scalable. This is an opportunity to work on high-impact problems across the employee lifecycle, from recruiting and talent to workforce planning, analytics, and people intelligence, and to play a foundational role in defining the next generation of AI-powered HCM at SAP.

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.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: View email address on click.appcast.io.

For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program , according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.

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 $148,600 - $306,300 (USD) .The actual amount to be offered to the successful candidatewill be within that range, dependent upon the key aspects of each case which may include education, skills,experience, scope ofthe role, location, etc. as determinedthrough theselection 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 .

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

Location: Palo Alto, CA, US, 94304

Nearest Major Market: San Jose

Nearest Secondary Market: Palo Alto

Job Segment: Database, Scientific, Cloud, ERP, Computer Science, Engineering, Technology