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Workday · IT - Software Development

Principal, Data Scientist

India, Chennai · Job Posted May 04, 2026
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Job Responsibility

  • 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

Requirements

  • 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

Nice to have

  • 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
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