IT-SLE Operations Analyst

University of Connecticut; Storrs-Mansfield (CT); Sur place; USD 77 000 - 94 000; Plein temps

Résumé du poste

The University of Connecticut is seeking a data/AI professional to bridge business intelligence, data analysis, and AI-enabled solutions for operational teams on a full-time basis at UConn Storrs. You will identify AI opportunities, develop AI-driven methods, and validate outputs to drive decision-making.

Applicants should have a strong analytics background, experience with large data sets, and proficiency in Python/SQL, with a focus on responsible AI and clear communication to non-technical

Qualifications

• Bachelor’s degree in information technology, business, data analysis or related field with six years of related experience.
• Or a Master’s degree with four years of related experience.
• Experience applying AI tools to improve real-world workflows.
• Experience performing statistical data analysis and modeling with large datasets.
• Experience evaluating AI solutions with responsible AI considerations.
• Experience taking an AI-enabled workflow from prototype to production.
• Ability to design, iterate, and document prompts/workflows; validate AI outputs.
• Ability to translate stakeholder needs into clear problem statements and AI-enabled solutions.
• Knowledge of AI/ML fundamentals and risks, including model evaluation.
• Proficiency in scripting/automation (e.g., Python/SQL/PowerShell/R).

Responsabilités

• Identify opportunities where AI may support efficiencies in workflows and decision-making.
• Develop and implement AI solutions within existing analytics processes.
• Prototype and test AI-enabled analytical methods for reporting and dashboards.
• Create low-code/no-code automations to streamline data prep, analysis, and reporting.
• Validate AI outputs for accuracy, bias, and relevance before use.
• Collaborate with data engineers to operationalize repeatable processes.

Connaissances

AI workflow integration

Statistical analysis & modeling

Responsible AI practices

Prototype to production AI

Prompts/workflows design

Stakeholder problem statements

AI/ML fundamentals awareness

Scripting (Python/SQL)

Data privacy & security

Data storytelling to non-technical

Communication of findings

Formation

Bachelor's degree in IT/Business/Data Analysis

Master's degree + experience

Description du poste

Search #: 499834
Work type: Full-time
Location: UConn Storrs
Categories: Administrative Services

JOB SUMMARY

Serves as the bridge between business intelligence, data analysis, advanced analytics, and innovative AI solutions, incorporating AI into daily analytical processes and decision-making for operational teams. Performs data analysis and modeling to identify trends, patterns, opportunities, and solutions to operational and business problems, while leveraging artificial intelligence tools, automation, and advanced analytics to improve data exploration, statistical models, generate actionable insights, and support decision-making. This position leverages the practical integration of AI into existing operational workflows.

DUTIES AND RESPONSIBILITIES

Assess and Identify Areas of Opportunity for AI

• Identify the standard operational workflows, systems, and processes for an operational team and assess opportunities where AI may support efficiencies in workflow, data collection, analysis, and decision-making.
• Assess operational workflows, systems, and analytical processes to identify inefficiencies and opportunities for AI, automation, and process improvement, reducing manual effort, improving turnaround time, or enhancing analytical consistency.
• Perform ad hoc and recurring data analysis and modeling to address operational questions, identify trends and patterns, evaluate performance, and support decision-making.
• Collect, prepare, evaluate, and analyze data from multiple sources to identify opportunities, assess operational performance, and develop actionable insights.
• Meet with operational partners to determine feasibility of applying AI-assisted tools (e.g., copilots, large language models, automated analytics) to support data exploration, modeling, insight generation, and analytical efficiency.

Develop and Implement AI Solutions

• Partner with analysts to introduce AI-enabled methods into standard analytical practices.
• Translate business questions into AI-assisted analytical approaches, including natural-language querying, statistical analysis, model interpretation, pattern detection, and predictive or other analytical modeling.
• Prototype and test AI-enabled analytical methods that augment existing reporting, dashboards, and analysis workflows.
• Develop low-code or no-code automations within existing software that streamline routine data preparation, analysis, and reporting tasks.
• Apply and interpret statistical, mathematical, or predictive models, as appropriate, to support operational planning, evaluation, forecasting, and decision-making.
• Collaborate with data engineers or platform teams to operationalize repeatable analytical processes.
• Validate AI outputs for accuracy, bias, and relevance before use in decision-making.
• Integrate AI-supported reporting, trend detection, anomaly identification, and analytical modeling to support dashboards, reports, and ad-hoc analyses.

Communication and Stewardship of AI Solutions

• Collaborate with stakeholders to explain AI-supported insights, analytical findings, and modeling results in clear, non-technical language.
• Serve as a resource for responsible AI use, helping analysts understand appropriate use cases and limitations.
• Follow organizational standards for data governance, privacy, and responsible AI use.
• Document AI-assisted workflows, analytical methodologies, modeling assumptions, and sources to ensure transparency and reproducibility.
• Stay informed on emerging AI tools and techniques relevant to data analysis and modeling, recommending adoption when value-aligned.
• Supports technical projects as part of a project team.
• Evaluate internal systems for efficiency, problems, and inaccuracies.
• Performs related work as required

MINIMUM QUALIFICATIONS

1. Bachelors degree in information technology, business administration, data analysis or related field, and six years of related experience; or a Master's degree and four years of related experience.

• Experience applying AI tools to improve real-world workflows (e.g., analysis, drafting, summarization, customer support, knowledge search, or automation).
• Experience performing statistical data analysis and modeling using large datasets, with practical experience in understanding their use in making informed decisions.
• Experience evaluating and operating AI solutions (test cases/metrics, monitoring/logging) with a strong grounding in responsible AI (privacy, security, bias, accessibility).
• Experience taking an AI-enabled workflow from prototype to pilot/production, including stakeholder feedback, documentation, and basic automation/API integration.
• Ability to design, iterate, and document prompts/workflows; validate AI outputs for accuracy, bias, and appropriateness before use.
• Ability to translate stakeholder needs into clear problem statements, success criteria, and practical AI-enabled solutions.
• Working knowledge of AI/ML and generative AI fundamentals, including common limitations and risks (e.g., model evaluation basics, hallucinations, and prompt sensitivity).
• Proficiency with at least one scripting or automation approach (e.g., Python, SQL, PowerShell, R, or a low-code platform) to streamline and standardize processes.
• Knowledge of responsible AI, privacy, and security practices, including appropriate handling of sensitive data when using AI systems.
• Knowledge of statistical models, data analysis techniques, predictive modeling, and/or optimization.
• Experience communicating analytical findings to non-technical stakeholders.

PREFERRED QUALIFICATIONS

• Hands-on experience building AI-assisted solutions with large language models (LLMs), including prompt/workflow design and structured outputs.
• Familiarity with retrieval-augmented generation (RAG), semantic search, embeddings, and working with unstructured content (documents/knowledge bases).
• Experience applying advanced analytical, statistical predictive, or mathematical modeling techniques to evaluate operational performance, identify trends and patterns, and develop data-driven recommendations.

COMPENSATION AND BENEFITS

The hiring range for this position is $85,000. An offer of employment, if made, will be commensurate with the successful candidate’s skill and experience, as determined by the University.

For more information about benefits and other offerings available to University employees, we encourage you to review the Human Resources website and explore the sections under the Benefits & Leaves header at the top of the page. Under Benefits & Leaves, select Benefits to access an overview as well as additional information on topics such as paid time off, benefits, retirement, and other resources. As you explore these pages, please note that this position is covered by the University of Connecticut Professional Employees Association (UCPEA) and look for information specifically identified for UCPEA, as provisions may vary by employee group.

APPOINTMENT TERMS

This is a full-time, permanent position. The University offers a competitive salary, and outstanding benefits, including employee and dependent tuition waivers at UConn, and a highly desirable work environment. For additional information regarding benefits, please visit UConn Health Benefits and explore the sections under the Benefits & Leaves and Engagement & Learning headers. Other rights, terms, and conditions of employment are contained in the collective bargaining agreement between the University of Connecticut and the University of Connecticut Professional Employees Association (UCPEA).

TERMS AND CONDITIONS OF EMPLOYMENT

Employment of the successful candidate is contingent upon the successful completion of a pre-employment criminal background check.

All employees are subject to adherence to the State Code of Ethics.

All members of the University of Connecticut are expected to exhibit appreciation of, and contribute to, an inclusive, respectful, and diverse environment for the University community. The University of Connecticut aspires to create a community built on collaboration and belonging and has actively sought to create an inclusive culture within the workforce. The success of the University is dependent on the willingness of our diverse employee and student populations to share their rich perspectives and backgrounds in a respectful manner. This makes it essential for each member of our community to feel secure and welcomed and to thoroughly understand and believe that their ideas are respected by all. We strongly respect each individual employee’s unique experiences and perspectives and encourage all members of the community to do the same. All applicants will receive consideration for employment without regard to race, color, ethnicity, religion, age, sex, marital status, national origin, ancestry, sexual orientation, genetic information, physical or mental disabilities, veteran's status, status as a victim of domestic violence and/or sexual assault and/or trafficking in persons as defined by Connecticut law, prior conviction of a crime, workplace hazards to the reproductive systems, or gender identity or expression

The University of Connecticut is an AA/EEO employer including for Disability and Veteran status.

Advertised: Oct 29 2026 Eastern Daylight Time
Applications close: Nov 06 2026 Eastern Standard Time