Senior Data Scientist Job at Adtalem Global Education (Minneapolis)

Job Description

The Senior Data Scientist is a technical leader within the CDX Advanced Analytics team, bridging advanced analytical capabilities with strategic business objectives. This role focuses on designing, building, and deploying sophisticated machine learning models and AI solutions that drive student enrollment, retention, and success outcomes. The Senior Data Scientist partners with stakeholders to translate complex business challenges into actionable analytical frameworks and provides technical guidance to junior data scientists.

Job Responsibility

Design, build, and maintain production-grade machine learning models that address critical business questions related to student enrollment, retention, and success.
Conduct rigorous machine learning experiments using structured methodologies to evaluate model performance and identify optimal solutions.
Implement model monitoring and maintenance protocols to ensure continued accuracy and relevance over time.
Develop scalable data pipelines and feature engineering processes to support model development and deployment.
Drive innovation in applied AI and Generative AI (GenAI) solutions, exploring opportunities to integrate advanced AI capabilities into data science products and workflows.
Partner with senior leadership to understand strategic priorities and assess how data science capabilities can address organizational needs.
Translate business requirements into well-defined analytical problems with clear success metrics.
Present complex analytical findings and model insights to non-technical audiences, including executive stakeholders.
Provide technical mentorship and share best practices with Data Scientists and Associate Data Scientists.
Apply statistical methods to validate model performance and ensure analytical robustness.
Document methodologies, assumptions, and limitations to maintain transparency and reproducibility.
Stay current with emerging machine learning techniques and evaluate their applicability to organizational challenges.
Support the growth of analytical capabilities across the organization through knowledge sharing.
Performs other duties as assigned.
Complies with all policies and standards.

Requirements

Bachelor's degree in an area such as Data Science, Computer Science, Statistics, Mathematics, or related field. Required. Master's degree preferred.
Five (5) plus years of experience in data science, machine learning, or advanced analytics roles.
Five (5) plus years of proven experience with production-level ML models, data pipelines and/or applied AI.
Famililarity with cloud platforms (GCP, BigQuery, Vertex AI), AzureDevOps and reporting tool (Power BI, Tableau).
Experience delivering end-to-end data science solutions, including data collection, feature engineering, model development, deployment, and integration into business workflows.
Demonstrated success with agentic workflows and GenAI in data science product solutions
Strong analytical skills with a foundation in statistical techniques (e.g., regression, clustering, classification, Monte Carlo simulation).
Excellent understanding of machine learning techniques and algorithms, such as decision trees, RF, XGBoost, LightGBM, etc.
Advanced skills in programming and coding, data science toolkits, and query languages (e.g., Python and SQL).
Demonstrated experience with data analysis tools and platforms such as GCP (incl. Vertex AI and BigQuery) and SQL Server.
Knowledge and familiarity with Power BI, Tableau, or comparable reporting and visualization platforms.
Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
Track record of helping organizations to leverage analytics to achieve documented business improvement.
Proven project management and people development skills.
Superior written and verbal communication skills including influencing and consensus building. Ability to explain technical concepts to non-technical audiences.
Ability to work in a dynamic and cross-functional environment, where multiple conflicting objectives need to be prioritized and achieved.
Ability to process ambiguous and/or seemingly conflicting data or information to create “one version of the truth.”