Staff Data Scientist
OktaBellevue, Washington; San Francisco, CaliforniaPosted 19 March 2026
Job Description
Get to know Okta
Okta is The World’s Identity Company. We free everyone to safely use any technology, anywhere, on any device or app. Our flexible and neutral products, Okta Platform and Auth0 Platform, provide secure access, authentication, and automation, placing identity at the core of business security and growth. At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box - we’re looking for lifelong learners and people who can make us better with their unique experiences.
Join our team! We’re building a world where Identity belongs to you.
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 looking for a Staff Product Data Scientist to join our Data Insights team. This role will lead the strategy, development, and operationalization of advanced analytics and machine learning solutions that power data intelligence for Okta’s Product Management teams, uncovering actionable insights on customer behavior, product engagement, and opportunities that will drive our product growth strategy. You’ll define the long-term data science roadmap while partnering closely with Okta’s diverse Product Management teams and executive leadership.
What you’ll be doing
Strategic Product Influence: Collaborate closely with Product Managers and leadership to provide insights that will help drive product strategy and roadmaps, ensuring decisions are grounded in a data-driven approach.
Advanced Analytics and Modeling: Build and deploy statistical and machine learning models (e.g., predicting churn, lifetime value, feature adoption) to forecast user behavior and product growth opportunities in order to help influence roadmap decisions.
Deep-Dive Insight Generation: Conduct thorough exploratory analysis on extensive, complex datasets to uncover key drivers of user adoption and engagement, identifying unseen opportunities for significant product improvement.
Data Ecosystem Partnership: Work with data engineering, analytics engineering, and data analysts to shape and enhance the foundational data infrastructure necessary for scalable ML and advanced analytics initiatives.
Data Preparation and Curation: Develop and construct usable data sets by integrating and manipulating information from various disparate data sources as needed.
Executive Communication and Influence: Translate intricate data insights into clear, compelling narratives for executives, product managers, and engineers, effectively influencing crucial business and product decisions.
What you’ll bring to the role
7+ years of experience in data science or ML, including 3–5 years in a senior, staff, or technical leadership role.
Deep understanding of product analytics and data science frameworks, with a proven history of designing and analyzing product data to solve complex, ambiguous business problems and deliver measurable results.
Demonstrated ability to apply cutting-edge AI tools to accelerate the discovery of deep, actionable insights from complex product data.
Demonstrated ability to translate data insights into product impact and formulate strategic, data-driven recommendations.
Deep expertise in machine learning algorithms (supervised, unsupervised, NLP, forecasting, optimization) and statistical modeling.
Strong proficiency in Python, SQL, and leading ML libraries.
Excellent communication skills and a proven ability to influence Product and executive partners.
And extra credit if you have experience in any of the following!
Experience in high-growth SaaS, cybersecurity, identity, or enterprise software environments.
Prior ownership of ML platform/tooling decisions and evaluations.
Experience enabling self-serv ... (truncated, view full listing at source)
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