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About the Role

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.

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.

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.
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.
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.
Exposure to or hands-on experience with GenAI and LLM applications is strongly preferred.
Must be able to travel occasionally should a business need arise.
Ability to work onsite in Corporate or Campus location (in a typical office environment) may be required.
If offsite or hybrid role, must have access to work in setting which enables meeting all requirements of the role.
Faculty and Federal Work Study roles require access to work in setting which enables meeting all requirements of the role.
This role may require lifting, however reasonable accommodations will be provided.
Must be able to meet critical thinking and problem solving aspects aligned to job duties, as well as effectively communicating with co-workers.
Must be able to work more than 40 hours per week when business needs warrant.
Able to access information using a computer.

Skills

Machine Learning
Generative AI
LLMs
CI/CD
Airflow
Power BI
SQL
Python
R
Prompting
Embeddings
NLP
Git
AWS
Azure
GCP
MLOps
Data Visualization
Data Analysis
Problem-Solving
Communication

Location

Corporate or Campus location

Work Type

Onsite
Hybrid
Remote

Experience Level

3+ years of experience in data science, advanced analytics, or a related field.

Education Level

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field required.

Salary/Compensations

$95,100.00 - $142,600.00

Benefits

Medical
Dental
Vision
Life and disability plans
Well-being incentives
Parental leave
Paid time off
Certain paid holidays
Tax saving accounts (FSA, HSA)
401(k) retirement benefit
Employee Stock Purchase Plan
Tuition assistance
Entertainment and retail discounts
Overtime pay, if applicable

About the Company

SEI is an equal opportunity employer committed to fostering an inclusive and collaborative culture where individuals can grow their careers and contribute fully.
We strive to attract talent with broad experiences, skills and perspectives.
We welcome applications from all.
While it is not typical for an individual to be hired at or near the top end of the pay range at SEI, we offer a competitive salary.
The actual base pay offered to the successful candidate may vary depending on multiple factors including, but not limited to, job-related knowledge/skills, experience, business needs, geographical location, and internal pay equity.
Our Talent Acquisition Team is ready to discuss your interest in joining SEI.

Equal Opportunity

SEI is an equal opportunity employer committed to fostering an inclusive and collaborative culture where individuals can grow their careers and contribute fully.
We strive to attract talent with broad experiences, skills and perspectives.
We welcome applications from all.