{"id":1196591,"url":"https://alion.io/job/sap-principal-data-and-applied-scientist","title":"Principal Data and Applied Scientist","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":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Montreal, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":87000,"max_usd":179000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":14},"experience_years_min":8,"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":"Function Calling","optional":true},{"name":"Multi-Agent Systems","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.\nData and Applied Scientist\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.\nWhere you belong\nYou will be part of Data Labs within the CX Office of the CTO, a strategic organization embedded in SAP Customer Experience. We define the AI strategy and architecture vision for next-generation CX solutions and ensure seamless integration across the SAP ecosystem. Our team works collaboratively across SAP product units, engages deeply in technology strategy, and partners closely with customers and external communities. We strive to create meaningful impact through world-class architecture, innovation, and industry-driven expertise.\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\n8+ 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\nExperience applying AI and semantic modeling to CX or Retail use cases such as personalization, pricing, product discovery, demand forecasting, or customer data unification across B2B and B2C contexts.\n\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.\nSAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward 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 combined range for this position is 144600-322500CAD. 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. A summary of benefits and eligibility requirements can be found by clicking this link: www.SAPNorthAmericaBenefits.com.\nDue to the nature of the role, which involves global interactions with SAP entities, as well as with employees and stakeholders in Canada, functional proficiency in English is required for positions based in the Quebec.\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: 459687 | 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":9757,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Equity","Flexible schedule"],"hiring_locations":[{"name":"Canada","iso":"CA","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":30,"band":"fade","label":"Fading","p_open":1,"p_active":0.673,"p_room":0.45,"age_days":29,"expected_fill_days":18,"reasons":["conf:0","win:tail","comp:brand"],"computed_at":"2026-09-25T00:02:21Z"},"pay":null,"html_url":"https://alion.io/job/sap-principal-data-and-applied-scientist","json_url":"https://alion.io/job/sap-principal-data-and-applied-scientist.json","meta":{"generated_at":"2026-09-25T00:02:21Z","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":58,"day_limit":5000,"remaining_today":4942,"minute_limit":60,"resets_at":"2026-09-26T00:00:00Z"}}}