Data Scientist II

Strayer Education, Inc.•Minneapolis, MN

2d•$95,100 - $142,600•Hybrid

About The Position

The Data Scientist II leverages machine learning and Generative AI (LLMs) to deliver scalable, data-driven solutions that improve business performance and decision-making. This role builds and deploys predictive and LLM-based models using modern tools (CI/CD, Airflow), develops impactful insights through strong analytics and Power BI visualizations, and partners with stakeholders to identify high-value opportunities. The ideal candidate has strong analytical skills, a keen eye for data, and a passion for applying AI to real-world problems.

Requirements

Strong proficiency in SQL and Python, or R.
Hands-on experience developing and deploying machine learning models.
Experience with Generative AI and LLMs, including prompting, embeddings, and NLP-related use cases.
Experience with CI/CD pipelines, Airflow, and workflow orchestration.
Strong experience with Power BI or similar data visualization tools.
Excellent analytical and problem-solving skills with strong attention to detail.
Strong data intuition and the ability to identify patterns, anomalies, and meaningful insights.
Ability to communicate complex analytical and AI concepts clearly to technical and non-technical audiences.
Experience with version control tools such as Git and collaborative development practices.
Ability to work independently and effectively in ambiguous environments.
3+ years of experience in data science, advanced analytics, or a related field.
Proven experience building and deploying machine learning solutions in production.
Experience applying statistical analysis and predictive modeling.
Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field required.

Nice To Haves

Exposure to or hands-on experience with GenAI and LLM applications is strongly preferred.
Experience with cloud platforms such as AWS, Azure, or GCP.
Experience operationalizing LLM-based solutions in production environments.
Familiarity with MLOps and model lifecycle management.
Demonstrated passion for AI innovation and continuous learning.

Responsibilities

Deliver measurable business impact using machine learning and GenAI/LLM-driven solutions.
Improve operational performance through scalable, production-ready analytics.
Develop and maintain a suite of Power BI reports and dashboards to enable informed, data-driven business decisions.
Enable smarter decision-making through data storytelling and visualization.
Identify and implement high-value GenAI use cases across the organization.
Promote responsible and effective use of AI and advanced analytics.
Mentor junior team members and help elevate overall team capabilities.
Analyze and integrate large, complex datasets from multiple sources, with cloud environments preferred.
Design, build, and deploy machine learning models and LLM-powered solutions.
Develop GenAI use cases such as text classification, embeddings, summarization, and decision-support tools.
Productionize models using CI/CD pipelines and orchestrate workflows using Airflow DAGs.
Monitor model performance, maintain documentation, and support governance, reliability, and ongoing model maintenance.
Translate analytical findings into clear and actionable business insights for technical and non-technical audiences.
Build dashboards and visualizations using Power BI to track KPIs, trends, and model outcomes.
Partner with stakeholders to identify opportunities for advanced analytics and AI adoption.
Apply strong data validation and quality checks to ensure data accuracy, completeness, and integrity.
Support ethical AI practices, data privacy requirements, and governance standards.
Mentor junior data scientists and contribute to team best practices and standards.