{"id":1196600,"url":"https://alion.io/job/sap-data-science-expert","title":"Data Science Expert","company":{"id":80,"name":"SAP","domain":"sap.com","url":"https://alion.io/company/sap-software-solutions","size_band":"5000+","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Enterprise Apps","role_family":"Enterprise Apps","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":62000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":505},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"SAP HANA","optional":false},{"name":"Scikit-learn","optional":false},{"name":"ServiceNow","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"ABAP","optional":true},{"name":"Function Calling","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"SAP BTP","optional":true},{"name":"Tool Use","optional":true}],"status":"live","first_seen_at":"2026-08-27T00:00:00Z","employer_posted_date":"2026-08-27","last_verified_at":"2026-09-24T23:45:53Z","board_verified":true,"closed_at":null,"days_open":29,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":29},"description":"We help the world run better\nAt 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.\nThe context engine that makes AI enterprise ready.\nAnyone 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.\nWhat you'll build\nThe 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.\nDesign and maintain enterprise ontologies and semantic models that 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.\n\nBuild AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production.\n\nDevelop AI capabilities including generative AI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets.\n\nLeverage SAP's deep data and process context including 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.\n\nWork with cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP to support reliable, scalable AI workflows.\n\nPartner across product, engineering, business, and customer-facing teams to translate ambiguous business challenges into concrete AI solutions from concept through deployment and continuous improvement.\n\nApply machine learning, deep learning, and statistical modeling to develop and evaluate AI solutions using real-world enterprise datasets.\n\nWhat you'll bring\nRequired Qualifications\n10+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.\n\nMaster's or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field\n\nHands-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.\n\nHands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.\n\nStrong Python and SQL skills with production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.\n\nProven track record deploying and operating AI/ML solutions in production including handoff, lifecycle support, and continuous improvement.\n\nExperience with big data infrastructure and cloud environments Databricks or equivalent, plus at least one major cloud (AWS, Azure, or GCP).\n\nExcellent communication and stakeholder management skills, with the ability to work cross-functionally in agile environments.\n\nPreferred Qualifications\nDeep working knowledge of SAP data models, metadata structures, and core business processes end-to-end. (SAP knowledge is a strong accelerator)\n\nHands-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.\n\nDeep expertise across the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) and/or property graph query languages (Cypher, GQL).\n\nDeep expertise in machine learning and deep learning, with experience developing, evaluating, and improving models on real-world datasets.\n\nExperience with agentic AI, reasoning frameworks, planning, orchestration, tool use, or multi-agent architectures.\n\nExperience contributing to reusable AI platforms, foundation model initiatives, or shared AI services adopted across multiple product areas.\n\nAbility to design upper-level and mid-level ontologies aligned with industry standards and apply semantic interoperability frameworks across complex application landscapes.\n\nUnderstanding 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.\n\nExperience working with SAP SuccessFactors extensibility and integration technologies, including OData APIs, Integration Center, SAP BTP, and/or other SAP integration patterns.\n\nExperience 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.\n\nWhere you belong\nJoin 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.\n#dlhiring\nBring out your best\nSAP 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.\nWe win with inclusion\nSAP’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.\nSAP 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: .\nFor 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.\nQualified 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.\nSuccessful candidates might be required to undergo a background verification with an external vendor.\nAI Usage in the Recruitment Process\nFor information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.\nPlease note that any violation of these guidelines may result in disqualification from the hiring process.\nRequisition ID: 459675 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid","description_format":"text","description_chars":9673,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule"],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Cloud Computing","AI Agents","Supply Chain"],"lifecycle":[{"event":"open","at":"2026-09-24T18:48:59Z"}],"liveness":{"score":38,"band":"fade","label":"Fading","p_open":1,"p_active":0.684,"p_room":0.55,"age_days":29,"expected_fill_days":22,"reasons":["conf:1","win:tail","comp:brand"],"computed_at":"2026-09-25T01:14:31Z"},"pay":null,"html_url":"https://alion.io/job/sap-data-science-expert","json_url":"https://alion.io/job/sap-data-science-expert.json","meta":{"generated_at":"2026-09-25T01:14:31Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1199,"day_limit":5000,"remaining_today":3801,"minute_limit":60,"resets_at":"2026-09-26T00:00:00Z"}}}