Forward Deployed Data and Applied Sciences (Chief) Expert

SAP•Stanford, CA

1d•$274,300 - $609,200•Hybrid

About The Position

In this role, you define and lead complex, high impact data science and applied AI initiatives that translate business strategy into scalable analytical solutions while embedded directly within customer environments and fast-moving delivery teams. You combine cloud native software engineering, enterprise data engineering, and production grade AI capabilities to solve complex real world business problems at speed. Acting as a trusted technical authority and strategic advisor, you guide senior stakeholders and cross functional teams from problem framing through delivery and measurable value realization. Your work directly influences enterprise level decisions by applying advanced modeling, machine learning, and AI techniques to the most complex and business critical challenges across customer and internal contexts. You set direction, standards, and best practices for excellence in data and applied science.

Requirements

Demonstrate a proactive approach to leveraging AI in everyday workflows, ensuring high-quality outputs through thoughtful context design and system integration.
Deep expertise in data science, applied statistics, and machine learning, with end-to-end ownership from problem framing through deployment and value measurement.
Proven ability to lead and govern complex, business-critical initiatives in high-ambiguity, high-impact environments.
Proven ability to work in an Agentic AI context, shaping and applying AI agents that act autonomously within defined boundaries, collaborate with human stakeholders, and deliver measurable business outcomes in customer-centric environments.
Strong command of modern analytics and ML technologies, including advanced modeling, large-scale data processing, and AI-driven approaches (e.g. NLP, generative AI).
Exceptional stakeholder communication and advisory skills, with the ability to influence and guide senior executives.
Recognition as a thought leader or "go-to" expert in data and applied science, both internally and externally.
Expertise in designing scalable end-to-end data pipelines and ETL/ELT architectures
Strong expertise in enterprise data modelling, orchestration, and system integration
Advanced proficiency in Python and SQL for large-scale data engineering
Hands-on experience with PySpark, Databricks, and distributed data processing
Expertise in workflow orchestration using Airflow and similar platforms
Strong experience with SAP HANA and enterprise-grade data platforms
Proficiency in lakehouse and columnar storage technologies such as Parquet and Delta Lake
Experience implementing real-time streaming architectures using Kafka or equivalent technologies
Strong focus on data quality, governance, compliance, and PII management
Expertise in applying CI/CD, Docker, and Git within modern data engineering workflows

Responsibilities

Own the delivery of complex, multi-dimensional data science and applied AI programs aligned with business strategy and financial objectives.
Act as the chief technical authority for advanced analytics, machine learning, and applied AI across domains, setting standards for quality, rigor, and scalability.
Design, oversee, and govern advanced data models, algorithms, and ML/AI systems, ensuring enterprise-grade robustness and real-world impact.
Translate ambiguous, strategic business challenges into clear analytical approaches, success metrics, and decision frameworks.
Partner with senior business, product, and engineering leaders to influence strategy, roadmaps, and investment decisions through data-driven insights.
Embed directly into customer projects and fast moving cross functional teams to rapidly understand business processes, technical landscapes, and operational challenges.
Represent SAP externally as a recognized expert, building trusted relationships and strategic partnerships with customers and stakeholders.
Mentor and guide senior data scientists, fostering innovation, technical excellence, and professional growth across the community.
Lead strategic, customer-facing engagements by partnering with senior stakeholders to shape high-value AI and data science initiatives and drive the co-creation and delivery of enterprise-scale solutions with measurable business impact.