Sr Product Data Scientist

Workday•Vancouver, BC

8d•CA$124,400 - CA$186,600•Hybrid

About The Position

Workday is seeking a Senior Product Data Scientist to partner with the Workday Data Cloud business. This role involves providing analytical rigor and business insights to a fast-growing, consumption-based product line. The Senior Product Data Scientist will be the investigatory lead, diving into raw business data to find root causes and deliver actionable conclusions. This role requires becoming a subject-matter expert in Workday Data Cloud's business data landscape, contributing to a shared knowledge base that aids future analysis and AI-assisted tooling. The position operates at the intersection of Workday's Data Cloud business, partnering with the Data Cloud organization, including SVP/GM, Product Management, Engineering, and GTM teams.

Requirements

8+ years of experience with advanced analytics, statistical modeling, and/or data science
8+ years experience simplifying complex technical concepts for diverse stakeholders.
6-8 years experience working autonomously in a highly matrixed, collaborative corporate environment.
5+ years experience in business/product analytics, applied data science, or a related quantitative role, ideally supporting a product or platform organization.
5+ years experience in enterprise BI platforms (e.g., Tableau, Sigma)
Strong SQL and data-modeling skills; comfortable working directly in raw, partially documented, or partially instrumented datasets.
Working familiarity with cloud data pipelines/ETL concepts (e.g., Airflow) sufficient to partner effectively with data engineering and platform product management teams.
Strong communication and data storytelling skills
Degree in a quantitative field (Computer Science, Engineering, Statistics, Operations Research, Economics, or a related field) or equivalent practical experience.
Understanding of product management fundamentals

Nice To Haves

Familiarity with front-end components or frameworks (e.g., React, Node.js, JavaScript) to help collaborate with engineering peers.
Experience with SaaS pricing analytics or usage-based/consumption pricing models specifically.
Strong project management skills
Experience applying organizational change management principles
Experience working within an Agile/Scrum framework.
Experience within the SaaS, cloud, or enterprise technology industries
Demonstrated experience designing, developing, and maintaining enterprise production-level data science-based products for business decision-making
Experience on AWS stack (Redshift, Sagemaker), scripting languages (Python and R)

Responsibilities

Serve as the business analytics domain expert for Workday Data Cloud, providing technical and strategic thought leadership.
Partner cross-functionally across Go-To-Market (GTM) and Product teams to develop end-to-end views of the business, connecting the dots between top-of-funnel demand growth, sales pipeline, and downstream product usage.
Translate complex data models into compelling narratives and stories (including interactive visualizations and executive presentations) that drive organizational clarity.
Operate directly with SVP/GM-level stakeholders, translating a stream of layered, high-velocity questions into structured analysis without needing fully scoped requirements up front.
Translate ambiguous business, data, and platform questions into simple and focused conclusions, independently and with strategic judgment.
Support consumption-based pricing and impact analysis for Workday Data Cloud, including sensitivity analysis, exploring new business models and driving business growth.
Navigate real data-maturity and instrumentation gaps with autonomy: identifying what already exists, what must be built, and when to escalate.
Contribute well-documented, curated data assets and context back into the shared knowledge base so that analysis compounds over time and can eventually be self-served.
Design and influence Workday Data Cloud internal business data connections, collaborating with Product Management and engineering teams on the design, scalability, and sustainability of associated pipelines.
Leverage strong data ETL and data processing expertise to manage multi-step flows across product telemetry and observability systems.
Demonstrate urgency and autonomy in problem-solving, proactively navigating cross-functional teams to identify and implement solutions for both known and emerging business challenges.