Pluralsight is looking to solve complex challenges, enhance product offerings, and deliver actionable insights that propel the business forward by leveraging deep expertise in data science, applied AI, and machine learning.
Requirements
- Deep understanding of machine learning algorithms, large language models (LLMs), and statistical methods, with practical experience deploying them in production.
- Proficiency in Python and interactive development environments (e.g., Jupyter or similar).
- Experience with modern data platforms for scalable data processing and analytics (e.g., Snowflake or other cloud data warehouses; dbt or similar frameworks; Airflow or other orchestration tools; Kubernetes or comparable container systems).
- Experience with modern ML platforms for development, deployment, and operations (e.g., PyTorch/TensorFlow; MLflow or similar experiment tracking; Hugging Face or vector databases for LLMs; MLOps practices at scale).
- Familiarity with model deployment and serving approaches, including use of large compute resources.
- Experience with data visualization and lightweight app frameworks (e.g., Streamlit or comparable) for communicating insights.
- Strong foundation in software engineering best practices (e.g., Git/GitLab, CI/CD, reproducibility).
Responsibilities
- Lead and execute end-to-end data science and AI projects, including problem definition, data exploration, model development, deployment, and evaluation.
- Develop and implement advanced machine learning and AI models and algorithms to drive product innovation, improve user experience, and optimize business processes.
- 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 clear visualizations and presentations.
- Collaborate with product managers, engineers, and business stakeholders to define project objectives, align on priorities, and ensure successful outcomes.
- Coach, mentor and develop data scientists, fostering a culture of technical excellence and continuous learning.
- Leverage deep expertise in data science, applied AI, and machine learning to solve complex challenges.
Other
- 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.
- Demonstrated ability to solve complex problems, mentor others, and influence across technical and product teams with clear communication and collaborative leadership.
