GENERAL INFORMATION

Location:
US-AZ - Phoenix
Position Type:
Full Time
Virtual Eligible:
Yes
Job Category:
Administration
Ref #:
6873

DESCRIPTION AND REQUIREMENTS

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.

MINIMUM KNOWLEDGE, SKILLS, AND ABILITIES):

• Master’s degree in a quantitative field such as statistics, computer science, mathematics, economics, or finance
• One (1) year of hands-on experience in the areas of inferential statistics, machine learning, simulation and predictive modeling, including proficiency with SQL, Excel and SAS, R or Python and knowledge of Microsoft SQL Server, statistical modeling and machine learning software (such as SAS Enterprise Guide, SAS Enterprise Miner, R Studio and Jupyter Notebook)

PREFERRED KNOWLEDGE, SKILLS AND ABILITIES :

• Mathematical/statistical skills including regression analysis (linear, logistic, parametric), forecasting models, factor/component analysis, decision trees, segmentation and cluster analysis
• Knowledge of distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.)
• Strong critical thinking and logical reasoning skills
• Strong verbal and written communication skills to effectively interact with internal and external customers and department staff
• Ability to follow verbal directions and instructions from the management to perform project work
  

  LI-remote

As an Equal Opportunity employer, we particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who demonstrate the ability to help us achieve our vision of a diverse and inclusive community.
If you are an active-duty military member seeking employment when off-duty, compliance with Department of Defense Joint Ethics Regulation, 5500-7-R, is required prior to starting employment with University of Phoenix. You are advised to contact your base Judge Advocate General to seek such approval and answer any questions.

1. Participate in the execution of complex statistical and machine learning analyses on large scale data sets to understand trends, discover relationships among variables and formulate predictive insights, conduct qualitative and quantitative analyses and build analytical models on data from existing databases, observations, and business and learning processes.
2. Resolve problems in business planning, management and optimization projects that are consistent with the University’s mission and business agenda/needs by applying analytical, statistical, machine learning, simulation, and/or experimentation methods.
3. Develop data models and perform statistical and machine learning analysis by developing and maintaining efficient SQL/Python/R code.
4. Deliver results generated from existing data science driven solutions that can bring business value and interpret project results.
5. Contribute in preparing reports and documentation on research findings, communicate model output both externally and internally, and present project results in a clear and effective manner through creative visualization.
6. Maintain and increase professional and technical knowledge and currency via self-research and by attending conferences, workshops and training. 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