Ops Research Scientist
Are you searching for a rewarding, fulfilling position that offers challenging work and the ability to make a big impact while working side-by-side with a team of fun, innovative people?
Ideally, would you like this position to be with an organization that makes a positive contribution to the world? If so we would love to hear from you!
About Us
University of Phoenix is a leading higher education institution founded in 1976 by Dr. John Sperling. Our mission is to improve the lives of our students, their families and future generations through higher education.
Our values (which hopefully you share) are : Brave. Honest. Focused.
Our University values and embraces all team members and their unique perspectives. We fundamentally believe in fostering an environment which deeply respects, celebrates, and actively encourages a diverse workforce.
We are committed to hiring and learning from those who share our passion to help others achieve their educational aspirations.
We offer excellent benefits, an effective recognition program, and outstanding learning and development tools, including tuition vouchers for employees and their qualified family members.
About the Position
An Operations Research Scientist develops and employs advanced simulation and / or predictive models to inform decision making and uses analytical methods and tools to solve complex business issues.
An Operations Research Scientist applies advanced statistical methods, machine learning, and optimization models to generate solutions and insights and presents the findings and results to the management and stakeholders.
What You’ll Do
1. Conduct qualitative and quantitative analyses and build AI, machine learning, statistical, and optimization models from existing databases, observations, and business and learning processes;
implement innovative decision technologies and AI techniques for business planning, management and optimization projects to generate solutions to University operations issues.
2. Process structured, unstructured and semi-structured data and apply data cleaning, data imputation and feature engineering methods prior to developing models.
Develop and employ simulation models and predictive models using machine learning, Natural Language Processing and statistical analysis methods;
perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data, and identify patterns.
3. Provide sound perspective on modeling approach, technique and tools in resolving the business problem; prepare and present reports and presentations on research findings to University leadership;
advise management and other stakeholders regarding appropriate courses of action to take for the project objectives.
4. Assist business groups in program or process evaluation, review, and implementation.
5. Develop plans for and participate in publishing and presentation of research findings via scholarly journals and conferences in the field.
6. Maintain and increase technical knowledge and currency via self-research, reviewing journal and conference publications, and learning from other technology resources.
Research latest techniques and tools to continuously enhance the discipline.
7. Perform other duties as assigned or apparent.
NOTE : The primary accountabilities above are intended to describe the general content and requirements of this position and are not intended to be an exhaustive statement of duties.
Incumbents may perform all or most of the primary accountabilities listed above. Specific goals or responsibilities will be documented in the incumbents’ performance objectives as outlined by the incumbents’ immediate supervisor or manager.
Job Supervisory Responsibilities
None
What You Bring to the Table
MINIMUM EDUCATION AND RELATED WORK EXPERIENCE :
- Ph.D. in Industrial Engineering & Operations Research, Statistics, Mathematics, Computer Science, Management Science or other management / quantitative discipline
- Three (3) years of hands-on experience in statistical modeling, machine learning and artificial intelligence, that includes at least two (2) years of experience in at least one of the following programming languages : Python, R, Matlab, C++, C#, or Java;
and at least two (2) years of experience in data query using relational database systems (e.g., Microsoft SQL Server and Oracle Database)
ADDITIONAL QUALIFICATIONS :
- Master linear and generalized linear models, time series analysis, and survival models (including proportional hazards model)
- Master machine learning methods (including tree-based models, support vector machines, neural networks, boosting, bagging, reinforcement learning, and clustering), deep learning libraries (e.
g., TensorFlow, Keras, and PyTorch), and natural language processing
- Experience in cloud computing environments (e.g., AWS, Azure, and GCP) and distributed data systems (e.g., Hadoop and related technologies of Spark and Hive)
- Experience in using optimization methods (including linear, integer, mixed-integer, quadratic, and combinatorial programming) and solver libraries such as CPLEX, AIMMS or frontline Solvers
- Strong verbal and written communication skills to present project results in a non-technical manner to the team and stakeholders
- Knowledge of applicable business and learning systems, in conjunction with proficient knowledge in operations research techniques