Staff Data Scientist

The Technology, Data, and Intelligence Team

Okta is the leading independent identity provider. The Technology, Data, and Intelligence (TDI) organization is the engine that powers Okta's global workforce, providing the technology and systems that enable our employees to do their best work.

The Staff Data Scientist Opportunity

We are seeking a highly experienced Data Scientist to lead the strategy, development, and operationalization of advanced analytics and predictive insights that power our Go-To-Market (GTM) motion. This role will operate as a senior technical and thought leader within the Enterprise Data & Insights organization, helping steer the evolution of data science capabilities across the company.

You will be responsible for architecting scalable data science solutions that influence revenue, pipeline performance, customer value, and strategic business decisions. This includes setting the long-term data science roadmap, shaping platform and tooling choices, and implementing robust MLOps practices to ensure repeatability, governance, and operational excellence. A key part of this role will be enabling a future-state citizen data science model through the creation of extensible frameworks, reusable assets, and self-service capabilities.

This is a high-visibility, impact-driven role that blends technical depth, product thinking, stakeholder partnership, and organizational leadership.

• Data Science Strategy & Leadership
  
  
  
  • Own the end-to-end data science vision and multi-year roadmap, aligning with GTM, Sales, Marketing, Customer Success, and Executive leadership.
  • Define and drive the evolution of the data science platform, including model development environments, feature stores, ML pipelines, and production deployment frameworks.
  • Establish and oversee MLOps standards, ensuring reproducibility, model monitoring, versioning, performance tracking, and continuous improvement cycles.
  • Lead governance frameworks for responsible and transparent ML usage across the organization.
  
  
  
  
• Advanced Analytics & Predictive Modeling
  
  
  
  • Build, deploy, and scale predictive models and optimization frameworks that impact revenue generation, pipeline health, customer engagement, and churn/retention.
  • Develop advanced analytics solutions including lead scoring, propensity to buy, churn and risk identification, and deeper insights and correlation analysis on company key performance indicators.
  • Partner closely with GTM leadership to translate business goals into analytical solutions and communicate complex findings in clear, business-centric terms.
  
  
  
  
• Technical Architecture & Full-Stack Development
  
  
  
  • Architect and implement full-stack data science workflows: data discovery, feature engineering, modeling, validation, deployment, performance measurement, and iteration.
  • Collaborate with data engineering to shape the data ecosystem (databases, pipelines, feature stores, compute infrastructure) required for scalable ML.
  • Deliver reusable libraries, templates, and tools to support a democratized, self-service analytics environment.
  
  
  
  
• Evangelism & Enablement
  
  
  
  • Mentor and guide data scientists, analysts, and cross-functional teams on ML best practices, capabilities, and opportunities.
  • Drive the foundation of a citizen data science program, enabling non-technical teams to leverage ML-powered insights safely and effectively.
  • Represent data science across executive forums, cross-functional initiatives, and enterprise programs.
  
  
  
  

What you'll bring to the role

• 7+ years of experience as a data scientist or machine learning practitioner, with at least 3-5 years in a senior or staff-level leadership role.
• Proven experience building full-stack data science solutions - from data ingestion and feature generation to model deployment and monitoring.
• Deep expertise in:
  
  
  
  
  • Machine learning algorithms (supervised/unsupervised, NLP, forecasting, optimization)
    Statistical modeling and experimental design
  • Python and relevant ML libraries (scikit-learn, TensorFlow/PyTorch, XGBoost, etc.)
    SQL and distributed data technologies
  
  
  
  
• Strong fluency with cloud-based analytics stacks (AWS, Azure, or GCP) and modern ML platforms (Databricks, SageMaker, Vertex AI, MLflow, etc.).
• Hands-on experience implementing MLOps, CI/CD for ML, and automated training/deployment pipelines.
• Excellent communication skills, with a proven ability to translate analytical insights into business impact.
• Demonstrated success influencing and partnering with Sales, Marketing, GTM Operations, or Customer Success organizations.

And extra credit if you have experience in any of the following!

• Experience in a high-growth SaaS, cybersecurity, identity, or enterprise software environment.
• Prior ownership of ML platform decisions and tooling evaluations.
• Experience building or enabling self-service analytics or citizen data science capabilities.
• Familiarity with GTM analytics concepts such as funnel modeling, pipeline forecasting, account scoring, customer lifetime value (CLV), and revenue intelligence.

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