Principal, Data Scientist

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

About The Team

The Deployment Adoption Platform (DAP) team in our Product & Engineering organization is actively looking for a seasoned, highly technical and mission-driven Principal, Data Scientist to define and build models to analyze customer usage and other data and provide insights that enable data-driven product development and decision making at Workday. This is an exciting cross-functional role where you will work in partnership with a variety of stakeholders including but not limited to Product, Engineering, Technology, Design, Community, Services, Solution Marketing, and Solution Management to empower them with data-driven actionable insights. You will uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, and design experiments that drive adoption and engagement of Workday’s products and help grow the business. You will execute key data science initiatives and drive the requirements to identify, explore, evaluate, and analyze new data sets for key insights to continuously improve adoption.

About The Role

• Lead the data science strategy for global deployment and adoption initiatives, driving faster, safer, and more predictable customer onboarding
• Architect and deliver advanced analytical, statistical, and machine learning solutions that optimize data migration, configuration validation, risk detection, and adoption outcomes across customer environments
• Partner with global stakeholders - including product, engineering, customer success, and implementation teams - to embed data-driven decisioning directly into deployment tooling and workflows
• Define success metrics and experimentation frameworks, establishing the leading indicators for customer adoption, time-to-value, and deployment quality across regions and industries
• Influence product roadmaps by translating complex data insights into actionable strategic recommendations for senior leadership and stakeholders

Basic Qualifications

• 12+ years of experience spanning data science, software engineering, and data platform architecture in large-scale, multi-tenant SaaS environments, with a strong foundation in distributed systems and enterprise platforms.
• Proven track record of architecting, implementing, and operating data-driven platforms across multiple (3–4+) enterprise products
• Hands-on expertise in building and scaling high-throughput data ingestion and processing systems, with demonstrated ability to solve for concurrency, latency, and cost efficiency.
• Strong proficiency in at least one core programming language (Python preferred), used for data pipelines, modeling, experimentation, and production ML systems.
• Demonstrated ability to operate effectively in a globally distributed team, collaborating across time zones and cultures with product, engineering, and customer-facing stakeholders.
• Comfortable navigating high ambiguity, exercising autonomy, and setting technical direction in fast-moving, enterprise environments.

• Solid grounding in big data and distributed query technologies (such as Apache Spark, Hive) for large-scale analysis and feature engineering.
• Hands-on experience applying AI/ML techniques to observability and operational data, including anomaly detection, root cause analysis, predictive alerting, and system behavior modeling.

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email [email protected].

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