Sr Data Scientist, AI Innovation

Workday
Pune
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 8-10 yearsSkills: ["Communication","Stakeholder collaboration","Data-driven decision making","Outcome orientation","Responsible AI mindset"]

Build and deploy production-oriented machine learning and agentic AI solutions for Workday’s Finance Transformation Office. Apply predictive analytics, statistical methods, and NLP to forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention. Work with large structured and unstructured data sources to create automated data pipelines, develop and evaluate models, monitor performance, and establish responsible AI and governance practices. Collaborate with Finance and engineering to translate insights into measurable business value.

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FursaFursa
Workday
Workday
3 days ago

Sr Data Scientist, AI Innovation

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Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Build and deploy production-oriented machine learning and agentic AI solutions for Workday’s Finance Transformation Office. Apply predictive analytics, statistical methods, and NLP to forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention. Work with large structured and unstructured data sources to create automated data pipelines, develop and evaluate models, monitor performance, and establish responsible AI and governance practices. Collaborate with Finance and engineering to translate insights into measurable business value.
Location: Pune
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Apply data science and machine learning to deliver forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention capabilities for finance problems.
  • •Develop agentic AI solutions and orchestrated workflows that automate end-to-end processes and generate proactive recommendations.
  • •Build robust data pipelines and automated processes to cleanse, integrate, validate, and evaluate large datasets from disparate sources.
  • •Evaluate model performance in production, monitor solutions for bias or drift, and continuously improve quality and reliability.
  • •Partner with Finance, product teams, and service organizations to define success metrics and run data-driven experiments, translating insights for technical and non-technical stakeholders.

Key Requirements

  • •8-10 years designing and developing methods to consolidate and analyze structured and unstructured data sources.
  • •Build and deploy machine learning models for forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention.
  • •Develop agentic AI solutions that reason over finance data, orchestrate workflows, automate repetitive processes, and surface proactive recommendations.
  • •Create data pipelines to cleanse, integrate, validate, and evaluate large datasets from multiple sources.
  • •Establish best practices for responsible AI, model governance, data quality, privacy, and secure use of financial information.
Experience:8-10 years
Skills:CommunicationStakeholder collaborationData-driven decision makingOutcome orientationResponsible AI mindset
Tech Stack:Data scienceMachine learningPredictive analyticsStatistical techniquesGenerative AILarge language modelsRetrieval-augmented generationRAGAI agentsWorkflow orchestrationNatural language processingNLPAnomaly detectionData pipelinesForecastingClassificationOptimizationFraud prevention

Company Brief

Workday
Provides cloud-based enterprise applications for human capital management, financial management, payroll, and analytics. Delivers unified HR and finance software suites to large organizations, enabling workforce planning, talent management, payroll, and financial reporting.
Industry: HR Tech
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Pleasanton, United States
Founded: 2005
WebsiteLinkedIn