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Data Scientist

Pluralsight

hybridmidpermanentdata United States Today via LinkedIn

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Tags

Data ScienceMachine LearningPythonSQLNLPLLMsCausal InferenceRecommender SystemsForecastingStakeholder Communication

About the role

Role Overview

As a Data Scientist on Pluralsight’s Data Science & Machine Learning (DSML) team, you’ll deliver strategic projects from experimentation through implementation. You’ll use data science, machine learning, and statistical analysis to solve complex problems, improve product offerings, and provide actionable insights.

Responsibilities

  • Develop algorithms and models from prototyping through to customer-facing solutions.
  • Collaborate with data scientists and machine learning engineers to define technical product requirements.
  • Define performance metrics, build test suites, and create visualizations to monitor model behavior.
  • Communicate complex, data-driven insights and recommendations to technical and non-technical stakeholders.

Requirements

  • 3+ years of hands-on, professional experience in data science/ML or a related field with a track record of impactful delivery.
  • Strong SQL and Python skills.
  • Experience self-managing projects and delivering on commitments.
  • Ability to solve complex problems and work effectively with stakeholders to resolve ambiguity.

Nice-to-Haves / Experience Signals

  • Work in NLP, LLMs, and causal inference/imprints.
  • Hands-on experience with search, recommendation engines, forecasting, and causal inference.
  • Detailed knowledge of data structures and database operations.

Location / Work Model

  • Remote role.
  • Candidates within 45 miles of the Westlake/Dallas, TX office should work on-site Tuesday–Thursday, with remote flexibility on Mondays and Fridays.

About Pluralsight

Pluralsight provides a learning platform focused on accelerating technology skills for the modern workforce. It serves companies, government organizations, and individuals with curated content, skill assessments, and hands-on learning experiences across areas like AI, cloud, cybersecurity, software development, and machine learning.

Scraped 5/15/2026

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