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Director, Analytics Intelligence – HigherEdJobs | #education | #technology | #techjobs


SUMMARY:

Reporting to the Vice President of Predictive Analytics, the Director, Analytics Intelligence partners
with operational groups across the organization on identifying opportunities for analytic solutions to enable operational enhancements and
improvements that will maximize the creation of optimal student outcomes. The Predictive Analytics team analyzes, designs, develops, and
deploys analytic solutions to support the entire organization. This role will lead the problem formulation, data analysis, solution design,
solution development, solution deployment, and operational implementation within the Predictive Analytics team supporting the entire
organization.

The analytical solutions will support the entire student journey while focusing on marketing, retention, placement,
tuition and scholarships, graduation rates, student learning, student engagement, and other relevant academic success factors to be used for
decision making related to enhancing student outcomes and academic excellence. This leader will collaborate with leaders across many
operational areas to ensure alignment between operational processes, data input/entry, and analytic solutions. A test, learn then pivot or
scale approach will be vital for success in this role.

Opportunity to join a fast-growing advanced analytics team aiming to provide
world class analytics to maximize student success. The Predictive Analytics supports the entire journey of our students from interested lead
to enrolled students to graduation to job placement in their chosen medical field of study. Come join a great team with a focused approach
to test, learn, pivot or scale our analytic products. The role will have a direct impact to ensure more qualified medical professionals are
available in the near future. Come make the world a little better place one query, one analysis, one model, and one impactful project at a
time.

ESSENTIAL FUNCTIONS AND RESPONSIBILITIES:

35% Complete in-depth analysis and create accurate problem
formulation while partnering with operational groups to validate findings. Develop both complex predictive and prescriptive solutions.
Publish validated operational and actionable analytical solutions to the end user and front-line educators utilizing operational systems,
Business Intelligence software, and other delivery points of analytical insights/solutions. Foster a culture of data driven decision making.

25% Lead the development, deployment, and operational implementation of both basic and advanced predictive models and analytic
solutions using Python, R, SAS, Keras, or Tensorflow including but not limited to:

  • Build, train, test and deploy operational
    predictive models for enrollment and student success outcomes.
  • Build, train, test and deploy operational predictive models for class
    analytics.
  • Build, train, test and deploy operational predictive models for faculty analytics.
  • Build, train, test and deploy
    operational predictive models as requested.
  • Supervise junior and senior analysts throughout the entire predictive modeling life
    cycle.
  • Provide operational predictive model outputs (scores, indices, percentiles) to be available for integration within
    operational systems including both Business Intelligence tools and end user interfaces/systems.

20% Design and write programs
and algorithms to train, test and develop complex analysis, predictive models, and detailed insights using Python, R, SPSS Modeler, SAS, and
other appropriate best practice tools.

10% Perform ad hoc requests to provide supervised and unsupervised trend analysis on student
academic and success data, recruitment and enrollment data, state board pre-licensure exams, financial and operational data.

10%
Query, extract and mine necessary large data from Oracle CVUE database, CRM, IR&A Data Warehouse, College Board, IPEDS, National Student
Clearing House, Common Dataset, and other utilities and sources. Be a champion of rigorous data integrity and collection across the
institution

EDUCATION:

Bachelor’s degree in statistics, economics, mathematics, engineering, or similar
quantitative field is required. Graduate degree highly desired.

KNOWLEDGE/EXPERIENCE:

7+ years of experience
in technical research, statistical work in the collection, compilation, and analysis of complex data including machine learning methods.

Demonstrated work experience in higher education or similar data driven industry including interpretation and presentation of
student, faculty, class, enrollment, and financial planning data is highly desired.

Demonstrated working experience of SQL/PLSQL
programming, Python Pandas, and Scikit-Learn will be given due consideration.

3+ years of experience of leading and supervising a
team of at least three data analysts or scientists. The supervisory experience requires recruiting, evaluating, coaching and optimizing
talents and staff in a strong statistical, analytic, data management, and reporting and data visualization line of work.

3+ years of
progressively responsible experience in advanced predictive model development including XGB, Random Forest, Neural Networks, Ensembles,
Clustering, PCA, NLP, etc.) using Python, R, or SAS.

7+ years statistical model development experience using either Python, R, or SAS
including the operational deployment and implementation support of the developed predictive models.



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