Director, Data Science

Company Description

At Adtalem Global Education, we seek to empower students and members to achieve their goals, find success and make inspiring contributions to our global community. Adtalem is a leading healthcare educator that partners with organizations to proactively address future workforce needs and empowers career development with access to world-class academic curriculums, certifications and training programs across the medical and healthcare industries.

Adtalem institutions and companies include: American University of the Caribbean School of Medicine, Chamberlain University, Ross University School of Medicine, Ross University School of Veterinary Medicine, and Walden University. (NYSE: ATGE; member S&P MidCap 400 Index) For more information, please visit adtalem.com.

Job Description

• Identifies and manages existing and emerging risks that stem from business activities and the job role.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.
• Follows written risk and compliance policies, standards, and procedures for business activities.
• Collaborates with other analytical leaders to fulfill the strategic direction of the business through data and information exploration, research of emerging technologies or analytical techniques and long-term defined/project specific strategic assignments.
• Oversees and carries out the exploration of promising new technologies, analytical methods and data sources (internal & external) that have potential to contribute to the enterprise.
• Partners with enterprise analytical and IT teams to build core capabilities and processes.
• Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts.
• Understands the business direction, and environment and strategies to identify and recommend solutions that influence decision makers and inspire change.
• Directs the design and construction of large and complex data sets from large amounts of structured and unstructured data (internal and external) to enable analytical solutions.
• Builds and leads a high performing team of experts in advanced analytics; develops team reputation as highly skilled experts in the field of data science.

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Qualifications

• Master's degree or PhD in Computer Science, Applied Mathematics, Quantitative Economics, Statistics, or related field OR 6 additional years of related experience beyond the minimum required may be substituted in lieu of a degree.
• Eight (8) years of experience in predictive modeling, large data analysis and computer science.
• Three (3) years of direct management experience.
• Experience in stochastic modeling, machine learning, and other advanced mathematical techniques (e.g., neural nets, simulation, graph analysis).
• Expert in at least one compiled language (e.g., Java, C) and one dynamic scripting language (e.g., Python).
• A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
• Extensive background in data mining and statistical analysis.
• Excellent pattern recognition and predictive modeling skills.
• Knowledge and application of Data Science principals and experience with data science methodologies.
• Experience with the following statistical and predictive modeling approaches: Gaussian Process; Markov Models; Hierarchical Clustering; K-Means; Linear Regression; Logistic Regression; Monte Carlo Simulation; Neural Networks.
• Deep technical skills, consulting experience, and business savvy to work with all levels and disciplines within our customers' organization.
• Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science.

Preferred Qualifications

• Experience in experimental design.
• Advanced knowledge of statistical methods, mathematics, and AI/ML algorithms including traditional general linear model (GLM) family models (including linear and logistic), tree-based methods (random forest, gradient boosted models), deep learning methods (neural networks, etc.), and general optimization methods (e.g., gradient descent, etc.).
• Knowledge in model performance evaluation techniques, metrics and validations strategies (nested-cross-validation, etc.).
• Expert in data visualization using Python/R and Tableau.
• Expert in communicating concepts, proposals, ideas and results to key decision makers.
• Expert in model testing, validation and CI/CD techniques.
• Knowledge and familiarity with Google Cloud Platform.