Senior Data Scientist- Finance & Spend, Data Labs

SAP SE; Bengaluru; On-site; INR 3,000,000 - 5,700,000; Full time

Job summary

SAP SE’s Data Labs unit seeks a Senior Data Scientist focused on Finance & Spend. You will build semantic layers, ontologies, and AI capabilities grounded in SAP data models, integrating data from enterprise sources to support reliable AI agents in critical finance processes.

You will lead design of knowledge graphs, RAG pipelines, embeddings, and production-grade ML workflows across Order-to-Cash, Procure-to-Pay, and related domains, collaborating with cloud platforms and stakeholder teams.

Qualifications

• Master's or PhD in CS, Applied Math, Statistics, Eng, or related field.
• Hands-on experience designing enterprise ontologies and semantic models.
• Experience with GenAI systems, RAG, embeddings, vector databases.
• Production-grade Python and SQL; ML libraries like PyTorch, TensorFlow, or scikit-learn.
• Experience deploying AI/ML in production and cloud environments (Databricks, AWS/Azure/GCP).

Responsibilities

• Design and maintain enterprise ontologies and semantic models.
• Build AI capabilities including RAG pipelines and vector databases.
• Develop AI capabilities using enterprise data and knowledge graphs.
• Leverage cloud platforms to support scalable AI workflows.
• Partner with product and engineering to translate challenges into AI solutions.

Skills

Knowledge engineering

Semantic data systems

Applied AI

Data science

Graph query languages

Python

SQL

ML libraries

Education

Master's/PhD in CS/Math/Stats/Engineering

Tools

Databricks

SAP Datasphere

SAP HANA Cloud

AWS

Azure

GCP

Job description

Senior Data Scientist- Finance & Spend, Data Labs

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.

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 agentsoperateon surface-level patterns, SAP agents areaccuratebecause they understand the real semantics of enterprise business master data, process flows, and domain relationships.You'llbuild and scale the layer that makes that possible.

Design andmaintainenterprise ontologies and semantic modelsthat give AI agentsaccurate, 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 knowledgegrounding thatmake SAP's agentsaccurateand 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 processcontextincludingSAP 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

Required Qualifications

• 5+ yearsof 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;proficiencyin 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 asPyTorch, TensorFlow, or scikit-learn.
• Proventrack recorddeploying 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.
• 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.
• Deepexpertiseacross the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) and/or property graph query languages (Cypher, GQL).
• Experience on Financial (example - accounting, close,reporting) andSpend (procurement, s2p, contracts) domain knowledge
• Deepexpertisein 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.

Whereyoubelong

You'lljoin the Data Labs unit, a tight-knit team turning AI from a promise into something Finance and Spend teams rely on every day,atglobal scale.You'llwork alongside curious engineers, thoughtful product minds, and applied researchers all focused on building AI that customers can trust in the highest-stakes business processes. The problems are real - money, risk, trust, and so is ownership.You'llstretch into new domains, see your models run, and help set the direction for SAP's AI in Finance and Spend. You will learnfasthave an excellent opportunity to own things end toend andbuild foundations others will stand on.

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 for 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: [e-mail].

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, 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.

Successful candidates might be required to undergo a background verification with an external vendor.

Location: Bangalore, IN, 560066

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