Job summary
Job post source
This job is directly from University of Phoenix
Job overview
The Operations Research Data Scientist at University of Phoenix designs and programs statistical and analytical solutions to optimize operations, strategies, and student learning.
Responsibilities and impact
The role involves translating business questions into quantitative analyses, developing models using machine learning and AI, coordinating pilots for new initiatives, collaborating with teams to deploy solutions, forecasting for planning, creating optimal short-term plans balancing service and cost, designing data visualizations, communicating results, advising management, and staying updated on industry trends.
Compensation and benefits
The position offers an annual salary of $98,739 with telecommuting options from anywhere in the U.S. Benefits details are not specified.
Experience and skills
Requires a Master's degree in Computer Science, Statistics, Industrial Engineering or related field with 1 year of data science experience in higher education; skills in SQL, data preprocessing, real-time model deployment, AWS cloud tools, R and Python for statistical analysis, A/B testing, and presenting data insights to non-technical stakeholders.
Work environment and culture
The job supports remote work 5 days per week and emphasizes collaboration with cross-functional teams and communication with leadership.
Company information
University of Phoenix is an educational institution focused on higher education and student learning optimization.
Job location and travel
The position is based in Phoenix, AZ with full telecommuting allowed anywhere in the U.S.
Application process
Candidates may apply online via the University of Phoenix career site or send a resume to the provided email with a reference code in the subject line.
Unique job features
The role includes working with advanced technologies like AWS Lambda, Redshift, SageMaker, and applying statistical and machine learning methods to real-world higher education challenges.
Company overview
The University of Phoenix is a for-profit institution that offers a range of online and on-campus degree programs tailored for working adults. They generate revenue primarily through tuition fees from their extensive catalog of undergraduate, graduate, and doctoral programs. Founded in 1976, the university has a significant history of pioneering online education and flexible learning formats. They are accredited by the Higher Learning Commission and focus on providing career-relevant education to a diverse student body.
How to land this job
Tailor your resume to emphasize your expertise in statistical analysis, machine learning, and experience with AWS tools such as Lambda, Redshift, and SageMaker, as these are key requirements for the Operations Research Data Scientist role at University of Phoenix.
Highlight your ability to translate complex business problems into quantitative analyses, your experience with SQL programming including nested queries, and your skills in data preprocessing, model deployment, and batch processing to align with the job description.
Apply to the position through multiple channels including the University of Phoenix corporate careers site at uop.avature.net and professional networks like LinkedIn to maximize your chances of visibility.
Connect with professionals working in data science or analytics divisions at University of Phoenix on LinkedIn. Start conversations by mentioning your interest in their recent projects or asking for advice on succeeding in data science roles within higher education.
Optimize your resume for ATS by incorporating keywords from the job description such as 'statistical analysis,' 'machine learning,' 'AWS SageMaker,' 'SQL nested queries,' 'A/B testing,' and 'data visualization' to ensure it passes automated screenings.
Use Jennie Johnson's Power Apply feature to automate tailoring your resume, identify the best application platforms, and find relevant LinkedIn contacts for networking, allowing you to focus more on preparing for interviews and skill development.
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