Artificial Intelligence/Machine Learning Data Engineer

at  University of Phoenix

GENERAL INFORMATION

Location:
US-AZ - Phoenix
Position Type:
Full Time
Virtual Eligible:
Yes
Job Category:
Information Technology
Ref #:
6867

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 EDUCATION AND RELATED WORK EXPERIENCE:

• Bachelor’s degree in a quantitative field such as statistics, computer science, or mathematics
• Three (3) years of professional experience as a Data Scientist, Data Engineer, or related work in advanced data analytics deploying AI solutions to cloud systems, which includes experience with best practices and techniques in the AI/ML field in one or more of the following areas: design and deployment of cloud services, data engineering, software development best practices, use of LLM’s and ML lifecycle, including managing experiments and monitoring for data quality issues and model performance degradation.

ADDITIONAL QUALIFICATIONS:

• Experience with advanced data analytics, algorithms, and machine learning frameworks, working with structured and unstructured data developing models to understand customer behaviors as well as advanced SQL programming skills and ability to tune performance of complex SQL statements
• Experience building and maintaining datasets for training models and managing vector data structures for Gen AI use cases
• Experience leveraging LLMs and the use of RAGs for advanced analytical solutions; working experience with Bedrock, Llama3, Open AI or Gemini is a plus.
• Experience with data modeling using integration patterns and standards to source data using one or more of the following data transformation tools such as Informatica, SSIS, SSAS, HVR, Airflow and/or GLUE
• Experience with Data Analytics workflows and technologies such as SQL, Python, S3, Redshift, Redshift Spectrum, Athena, RDS, Airflow, GLUE, Lambda, Quick-sight, Tableau, or Power BI
• Experience working in an agile or scaled agile environment
• Excellent oral and written communication skills to effectively interact with internal and external customers and department staff
• Ability to work in a team environment and act as a resource for less experienced resources and relay necessary information as appropriate
• Easily adapt to and embrace a fast moving and rapidly changing work environment
• Demonstrate a growth mindset and exhibit a highly collaborative workstyle
  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. Partner with Data Science & Strategy leadership to translate ambiguous business questions and concerns into
   specific quantitative questions that can be answered with available data and resolve problems in business planning,
   management and optimization projects that are consistent with the University’s mission and business
   agenda/needs.
2. Design, coordinate, and execute pilots and/or proof of concepts to assess the viability and business value of new
   initiatives and technologies, ensuring alignment with strategic goals.
3. Collaborate with cross-functional teams, including but not limited to data, analytics, governance, and legal, to
   deploy and implement data science and/or AI/ML solutions effectively, utilizing analytical models to derive
   actionable insights and recommendations, and ensuring compliance and alignment with organizational policies.
4. Evaluate the efficacy of new data sources and emerging analytics platforms, ensuring optimal utilization and
   alignment with business requirements.
5. Develop and implement continuous integration and continuous deployment (CI/CD) pipelines for machine learning
   models, ensuring seamless deployment and scalability.
6. Orchestrate tools for managing machine learning workflows, optimizing processes for efficiency and effectiveness.
7. Utilize advanced coding skills and applicable software to write complex queries, troubleshoot errors, and manage
   third-party libraries and virtual environments.
8. Create infrastructure and code using applicable software, contributing to the scalability and reliability of AI solutions.
9. Perform other duties as assigned or apparent.
   NOTE: The Primary Accountabilities above are intended to describe the general content and requirements of the 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 incumbents’ performance objectives as outlined by the incumbents’ immediate manager