Staff Data Scientist

Company: Pluralsight

Location: Location not specified (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-05-29

About this role

Job Description
As a Staff Data Scientist, you will play a pivotal role in our Data Science and Machine Learning (DSML) team, driving high-impact projects that shape our product experience and capabilities. You will leverage your deep expertise in data science, applied AI, and machine learning to solve complex challenges, enhance our product offerings, and deliver actionable insights that propel our business forward. This role requires a blend of technical mastery, strategic thinking, and leadership to foster innovation and deliver results.


Who You’re Committed To Being

  • You enjoy learning and are open to new ways of doing things.
  • You are not afraid to be yourself, experiment, make mistakes and learn from them, ask questions, or voice your concerns.
  • When communicating you are self-aware, insightful, and proactive.
  • You are a team member first and individual contributor second. You are aware that high-performing teams are only as strong as their weakest link.
  • You believe in continuous improvement and request frequent feedback from others.

What You’ll Do

  • Lead and execute end-to-end data science and AI projects, including problem definition, data exploration, model development, deployment, and evaluation.
  • Collaborate with product managers, engineers, and business stakeholders to define project objectives, align on priorities, and ensure successful outcomes.
  • Develop and implement advanced machine learning and AI models and algorithms to drive product innovation, improve user experience, and optimize business processes.
  • Coach, mentor and develop data scientists, fostering a culture of technical excellence and continuous learning.
  • Stay abreast of industry trends, emerging technologies, and best practices in data science, machine learning, and AI; evaluate and advocate for their adoption within the team and organization.
  • Communicate complex data-driven insights and recommendations to technical and non-technical stakeholders through ...

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