Data Scientist, Senior

Business And Data Analyst 3

Supports ASU's Actionable Analytics initiatives through the application of advanced data science, machine learning, statistical analysis, and artificial intelligence techniques, including the use of large language models (LLMs) and other foundation model technologies. Serves as a senior-level contributor responsible for designing, developing, validating, deploying, and monitoring analytical and AI-enabled solutions that address operational and strategic organizational needs.

Position Salary Range: $90,000 - $114,000 per year, DOE

Essential Duties:

• Leverages machine learning, artificial intelligence, large language models (LLMs), and other advanced analytical techniques to develop innovative solutions that address operational and strategic institutional needs.
• Promotes the responsible, ethical, secure, and compliant use of data science, machine learning, and artificial intelligence technologies in accordance with institutional policies and applicable regulations.
• Determines and develops advanced research design methodologies, data analysis approaches, statistical modeling procedures, machine learning solutions, and generative AI applications to meet operational and strategic organizational needs.
• As part of a team, conducts all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing deployment, monitoring, evaluation, and ongoing support.
• Selects and applies advanced statistical, predictive modeling, machine learning, large language model (LLM), and generative AI techniques to generate actionable insights and address complex organizational challenges using structured and unstructured data sources.
• Develops, deploys, integrates, and maintains statistical models, machine learning models, and AI-enabled solutions, including applications leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in development and production environments.
• Implements monitoring and evaluation processes for statistical models, machine learning models, and AI-enabled solutions to assess performance and enable continuous improvement.
• Collaborates with technical and non-technical stakeholders to translate business needs into analytical solutions and actionable recommendations.
• Creates and maintains technical documentation, analytical workflows, and model documentation.
• Supports the adoption of machine learning operationalization (MLOps/AIOps) practices, including version control, model deployment, workflow automation, and reproducibility.
• Learns, evaluates, and adopts new analytical methodologies, technologies, and tools to meet changing organizational needs.
• Presents analytical findings and recommendations through written reports, presentations, and data visualizations to technical and non-technical stakeholders.
• Provides technical guidance and mentorship to junior staff members and project teams as appropriate.

Desired Qualifications:

• Demonstrated knowledge of and experience applying generative AI and large language model (LLM) technologies, using a wide-ranging suite of structured and unstructured data sources and success outcomes, as well as advanced traditional and modern/machine learning predictive modeling methodologies.
• Experience conducting all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing, deployment, monitoring, evaluation, and ongoing support.
• Experience developing, validating, deploying, and maintaining machine learning models and AI-enabled applications, including solutions leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in cloud or production environments.
• Demonstrated knowledge of machine learning and AI best practices, including cross-validation, hyperparameter tuning, prompt optimization, model monitoring, performance evaluation, explainability, and responsible AI principles.
• Experience evaluating, selecting, and applying large language models (LLMs), foundation models, and generative AI technologies to support knowledge discovery, workflow automation, decision support, and business process improvement.
• Proficiency in Python and SQL, including experience leveraging libraries, frameworks, and APIs used for machine learning, data science, and generative AI applications.
• Demonstrated working knowledge of higher education data systems, including specialized data mining, natural language processing, knowledge discovery, and data visualization techniques.
• Experience using cloud-based analytics, machine learning, and AI services to develop, deploy, monitor, and support analytical and AI-enabled solutions.
• Experience using version control systems and collaborative development tools.
• Experience using data visualization tools and techniques to communicate complex analytical findings and insights.
• Demonstrated ability to clearly and accurately summarize findings and recommendations to technical and non-technical stakeholders to inform decision making.
• Demonstrated ability to lead complex analytical projects, prioritize competing demands, and complete projects on time and within scope.
• Demonstrated ability to work effectively both independently and collaboratively as part of a team.
• Demonstrated ability to translate stakeholder needs into appropriate, functional, and informative analytical and AI-enabled solutions.
• Experience mentoring or providing technical guidance to analysts, data scientists, or project teams.

Working Environment:

• Activities are performed in an environmentally controlled office setting subject to extended periods of staying in a stationary position, manipulating a computer 75 percent; required to traverse moderate distances to perform work 10 percent. Ability to clearly express oneself and effectively exchange information to perform essential functions. Frequent moving, transporting, and positioning up to 25 pounds 15 percent. Regular activities require ability to quickly change priorities, which may include or are subject to resolution of conflicts.

Department Statement:

Actionable Analytics, within the Office of the University Provost, advances student success by developing and supporting innovative enterprise analytics applications and data solutions for the Academic Enterprise. The department provides trusted data, data science solutions, actionable insights, and decision support tools that empower student success initiatives for ASU campus-immersion and digital-immersion students.

Driving Requirement:

Driving is not required for this position.

Location:

Campus: Tempe

Funding:

No Federal Funding

Instructions to Apply:

Current employees, student workers seeking staff opportunities, and students applying for student worker positions must apply directly through the Workday Jobs Hub.

To be considered, your application must include all of the following attachments:

• Cover letter
• Resume or CV

Multiple documents may be uploaded in the attachments section. Alternatively, applicants may combine all required materials into a single PDF for submission. Please ensure uploaded documents are clearly labeled and include your name.

Please ensure your resume includes all employment information in month and year format, for example 6/04 to 8/14, along with job title, job duties, and employer name for each position. Your resume should clearly demonstrate how your experience and background meet the minimum and desired qualifications for this position. Incomplete applications or missing required materials may not be considered.

Important: Do not withdraw your application to make edits. Once an application is withdrawn, it cannot be edited, reactivated, or replaced with a new submission. If you have questions or need assistance, please contact The Office of Human Resources Talent Acquisition before the posting close date.

Graduate Assistant, Intern and part-time positions are counted as half time for experience equivalency, meaning one year equals six months of experience.

Only electronic applications will be accepted for this position. By submitting an application, you confirm that the information provided is accurate and complete.

ASU Statement:

Arizona State University is a new model for American higher education, an unprecedented combination of academic excellence, entrepreneurial energy and broad access. This New American University is a single, unified institution comprising four differentiated campuses positively impacting the economic, social, cultural and environmental health of the communities it serves. Its research is inspired by real world application blurring the boundaries that traditionally separate academic disciplines. ASU serves more than 100,000 students in metropolitan Phoenix, Arizona, the nation's fifth largest city. ASU champions inclusive excellence, and welcomes students from all fifty states and more than one hundred nations across the globe.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other basis protected by law.

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