Staff Data Scientist

Pluralsight

1d•$153,900 - $220,000•Hybrid

About The Position

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.

Requirements

Advanced degree (Ph.D. or M.S.) in Computer Science, Statistics, Mathematics, Engineering, or a related field.
7+ years of experience in data science, applied AI, or machine learning, with a proven track record of delivering impactful, product-oriented projects.
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).
Demonstrated ability to solve complex problems, mentor others, and influence across technical and product teams with clear communication and collaborative leadership.

Nice To Haves

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).

Responsibilities

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 clear visualizations and presentations.