Senior Data Scientist delivering insights tying data to strategic execution for Workday's AI platform. Partnering with teams to analyze product adoption and optimize customer experience.
Responsibilities
Serve as the P&T domain expert in product adoption analytics, providing technical and strategic thought leadership.
Partner with key technical leaders and domain experts across Workday to map the data landscape, bringing transparency and data accessibility to key decision-makers.
Design and influence enterprise-wide adoption analytics data connections, collaborating with data engineering teams on the design, scalability, and sustainability of associated pipelines.
Translate complex data models into compelling narratives and data visualizations (including interactive dashboards and executive presentations) that drive organizational clarity.
Provide guidance on data trends, governance, and use cases to stakeholders across all levels of the organization.
Evangelize a customer-value-first approach to evaluating product health and adoption metrics.
Forensic data investigation to identify root causes and translate technical findings into simple and focused conclusions.
Leverage strong data ETL and data flow expertise to manage multi-step product telemetry and observability systems, ensuring data integrity.
Demonstrate urgency and autonomy in problem-solving, proactively navigating cross-functional teams to identify and implement solutions for both known and emerging business challenges.
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 enterprise BI platforms (e.g., Tableau, Sigma)
Familiarity with front-end components or frameworks (e.g., React, Node.js, JavaScript)
Experience working within an Agile/Scrum framework.
Experience within the SaaS, cloud, or enterprise technology industries
Proven track record of moving seamlessly between high-level strategy and technical execution
Strong communication and data storytelling skills
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)
Degree in a quantitative field (Computer Science, Engineering, Statistics, Operations Research, Economics, or a related field) or equivalent practical experience.
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