Data Science Leader - Finance

SAP SE; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

SAP SE in Bengaluru, India, is hiring for a senior AI/ML leadership role within the Data and Applied Science domain. The role focuses on building scalable AI foundations, knowledge graphs, and enterprise intelligence solutions that leverage SAP’s data platforms.

You will drive strategic AI initiatives, governance, and collaboration across global teams. Join a globally distributed, innovation-driven team, contributing to SAP's AI future while ensuring business value, stakeholder alignment, and

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'llbuild 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.

Whatyou'llbuild:

The Data and Applied Science team will build 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. 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 strongtrack recordof driving complex AI initiatives from concept to production across multiple teams and stakeholders.
• Ability to define technical strategy,establishteam priorities, and align AI investments with businessobjectives, 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, withdemonstratedsuccess hiring, coaching, andretainingtop 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.
• 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, andestablishingreusable enterprise AI platforms, governance frameworks, and shared services across multiple product areas.
• Thought leadershipdemonstratedthrough 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, metadatastructuresand core business processes end-to-end.
• Experience with the SAP data and AIplatformstack SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub.

KeyKnowledge and Abilities:

• 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 andestablishbest practices for ML Ops, LLM Ops, and model lifecycle management-making pragmatic build-versus-buy decisions across platform investments and technology roadmaps.
• Strong domainexpertisein ontology engineering, semantic technologies, metadata management, entity resolution, taxonomies, and knowledge representation, withdemonstratedexperience 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.
• Ability to conduct Machine Learning Model Training. Employees who excel in this skill haveexpertisein statistics, computer science, and mathematics, as well asproficiencyin software tools and programming languages.They are capable of selecting the right algorithm for a problem, preparing data sets, and testing model accuracy.
• Ability toutilizedeep 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.
• Ability to design, build, andmaintaininfrastructure for data collection, transformation, storage, and analysis. Employees who excel in this skill havea high levelof technicalexpertisein 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, andoptimizesemantic 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 deepexpertisein 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'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. 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'llfeel at home here.

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 your 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.

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

Employment Type: Regular Full Time

Expected Travel: 0 - 10%

Bangalore, IN, 560066

#LI-Hybrid

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