Data Science Senior Analyst, AI Engineer

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Job Title:

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Data Science Senior Analyst, AI Engineer

Department:

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Advancement | Business Intelligence

Position Overview

The Ohio State University’s Office of Advancement seeks a naturally curious, creative, and collaborative professional to serve as a Data Science Senior Analyst. This role offers the opportunity to use data science and emerging AI capabilities to help staff better understand alumni, donors, and other constituents, make more informed decisions, and improve how they accomplish their work.

The Office of Advancement brings together professionals in alumni and constituent engagement, fundraising, marketing, business planning, technology, analytics, and operations to build a community of lifelong champions who support and advocate for Ohio State.

The Data Science Senior Analyst works with business and technical partners to ask meaningful questions, uncover opportunities, and turn complex or ambiguous needs into practical data science and AI solutions.

The position applies customer analytics, predictive modeling, machine learning, generative AI, statistical methods, and other appropriate techniques to support fundraising, engagement, marketing, operational improvement, and strategic decision-making.

The work may range from identifying and prioritizing audiences and predicting future behavior to analyzing complex data and creating AI-enabled tools that make information and expertise more accessible to staff. This is an end-to-end role for someone who wants to see their work move beyond analysis or experimentation and become part of how people make decisions and perform their work.

The Data Science Senior Analyst coordinates and executes assigned solutions from discovery and prototyping through deployment, adoption, monitoring, and improvement. The role collaborates closely with intended users and technical partners to create solutions that are useful, understandable, maintainable, and responsibly designed.

The Data Science Senior Analyst independently performs complex analytical and technical work, recommends appropriate approaches, and receives general guidance on new projects or unfamiliar assignments. The role also serves as a consultative resource, helping partners understand what AI, data science, and analytics can accomplish, where their limitations lie, and how they can be used effectively.

The successful candidate will combine analytical and technical ability with curiosity, sound judgment, adaptability, attention to detail, and a commitment to collaboration, and will be comfortable learning evolving technologies and communicating complex concepts to technical and nontechnical audiences.

The role reports to the Associate Director, Data Science and collaborates with colleagues across Advancement, the university, and the Wexner Medical Center.

All members of Advancement are part of creating a culture that inspires an exceptionally multifaceted and talented team and are expected to exhibit The Ohio State University’s Shared Values . The Office of Advancement is committed to acting with kindness, respect, and integrity at all times and welcoming our colleagues’ ideas, voices, and perspectives, acknowledging that we are better together.

Duties and Responsibilities

55% - Coordinate and execute the discovery, technical design, development, testing, deployment, and ongoing improvement of assigned applied AI, machine learning, and advanced analytics solutions within established objectives and technical standards.

Develop predictive models, AI solutions, and analytical approaches that help Advancement understand alumni, donors, and other constituents; identify and prioritize audiences; recognize patterns and opportunities; and support informed engagement and fundraising decisions.

Design and build assigned AI-enabled tools, such as agents, intelligent search, decision-support tools, user-facing applications, workflow automations, conversational experiences, and reusable analytical services. Recommend methods based on documented business needs, available data, feasibility, risk, and intended outcomes.

Develop rapid prototypes and proofs of concept to assess feasibility, clarify requirements, demonstrate potential value, and gather early feedback from users.

Apply appropriate statistical, machine-learning, and analytical methods, which may include regression, classification, clustering, recommendation, forecasting, natural language processing, information retrieval, graph analysis, experimentation, or other techniques suited to the business need.

Apply techniques such as retrieval-augmented generation, prompt and context design, tool integration, structured outputs, semantic search, and human-in-the-loop review when appropriate. Develop user-facing applications, visualizations, documentation, and training materials in accordance with established accessibility and usability requirements and the needs of varied audiences.

Identify and evaluate internal and external data sources needed for assigned solutions, considering relevance, quality, limitations, appropriate use, and integration requirements. Recommend and coordinate with appropriate teams when acquisition or broader integration is needed.

Design, build, test, document, and maintain the data workflows, feature pipelines, evaluation datasets, and reusable data components needed to support assigned solutions. Collaborate with Data Science colleagues to ensure final data objects meet team standards. Assess and monitor the quality of data supporting assigned solutions, implement appropriate validation checks, and document relevant limitations.

Partner with data owners and technical teams to address issues requiring upstream or broader remediation. Develop, deploy, and maintain assigned solutions using approved development platforms and technologies, including Azure Databricks and Microsoft Azure, in accordance with established organizational standards and capabilities.

Develop evaluation plans and recommend acceptance criteria for assigned solutions, considering accuracy, relevance, reliability, robustness, fairness, usability, cost, latency, and expected business value. Use evaluation results to recommend the model, solution, or approach that best addresses the documented business need.

Monitor deployed models and AI solutions for performance, quality, drift, operational health, unintended outcomes, usage, cost, and continued business value. Document intended uses, limitations, assumptions, data dependencies, risks, evaluation results, and required human oversight.

Use approved AI-assisted and agentic development approaches, when appropriate, to support research, prototyping, coding, testing, debugging, documentation, and application development. Review and validate resulting work in accordance with established security, quality, and technical requirements. Design assigned solutions with consideration for reuse, scalability, performance, cost, and maintainability.

Develop reusable components and recommend practice improvements when supported by project needs and team standards.

30% - Build collaborative relationships with business partners, engage them throughout assigned solution lifecycles, and serve as a consultative resource on the practical use of AI, data science, and analytics. Gather and analyze information about business processes, user needs, pain points, decisions, and desired outcomes.

Translate complex or ambiguous problems into proposed requirements, success measures, and project scopes for review with appropriate stakeholders. Identify and assess AI, data science, and analytics opportunities based on business value, feasibility, risk, data readiness, cost, effort, dependencies, and alignment with established priorities.

Provide analysis and recommendations to support stakeholder and leadership decisions about solution approaches and portfolio prioritization. Involve intended users during design and development, gather feedback, conduct user acceptance and usability testing, and iteratively improve solutions.

Coordinate implementation of assigned solutions, including deployment planning, rollout, and early-life support, with guidance on new or unfamiliar projects. Assess how proposed solutions may affect business processes and collaborate with stakeholders on workflow design and implementation planning. Business leaders retain responsibility for approving and sustaining operational changes within their areas.

Plan for adoption in partnership with business partners, including strategies for stakeholder engagement, workflow integration, feedback, and monitoring of use and user experience. Create or coordinate audience-appropriate communications, one-pagers, demonstrations, methodology summaries, user guidance, training resources, and implementation documentation needed to support understanding and adoption.

Recommend and monitor measures of adoption, usability, efficiency, and business impact in partnership with stakeholders. Use findings and feedback to recommend improvements, communicate results, and support informed decisions about continued use and investment.

Coordinate ongoing activities for assigned solutions with business and technology partners, including documenting responsibilities for maintenance, monitoring, support, governance, adoption, improvement, transition, replacement, and retirement. Manage competing assignments and communicate tradeoffs, dependencies, risks, and resource needs.

Collaborate with the Associate Director and stakeholders to support the establishment and adjustment of priorities.

10% - Apply established university policies, approved technology standards, data governance requirements, and responsible AI practices to assigned solutions. Identify relevant privacy, security, fairness, accessibility, transparency, reliability, and appropriate-use considerations and engage appropriate specialists when additional review is needed.

Document and communicate the intended uses, limitations, risks, and recommended level of human review for assigned AI-enabled solutions. Follow established review and escalation processes and recommend additional review when warranted by a solution’s potential impact. Follow applicable requirements for intellectual property, licensing, data use, and AI-generated code and content.

Use approved platform capabilities and established documentation practices to maintain traceability, versioning, lineage, reproducibility, metadata, definitions, quality information, and usage guidance for assigned solutions.

Use evidence, experimentation, prototypes, and clear communication to explain the capabilities, limitations, risks, and practical applications of AI and data science and to support informed decisions and consensus among business and technical partners. Independently completes complex assigned work within established objectives, technical standards, and defined parameters.

Recommends technical approaches, resolves routine project issues, communicates risks and dependencies, and receives general guidance on new projects or unfamiliar assignments. Assess proposed work for business value, feasibility, risk, data readiness, effort, and dependencies and provide recommendations to support leadership and stakeholder portfolio decisions.

Participate in peer review and provide constructive feedback on code, pipelines, models, AI tools, evaluation methods, and documentation. Serve as an informal technical resource through knowledge sharing and guidance to less-experienced colleagues.

Apply established team practices for version control, code review, testing, reproducibility, deployment, monitoring, documentation, and maintainability within GitLab, Azure Databricks, and other approved environments. Recommend improvements based on documented project experience.

Provide technical input to Data Science and AI strategy, team standards, reusable patterns, responsible AI processes, and the team’s technology environment; support implementation within assigned work. Maintain knowledge of evolving practices in applied AI, data science, analytics, and software development. Apply relevant learning to assigned work and share practical recommendations and reusable approaches with colleagues.

5% - performs other duties as assigned

Required Qualifications

• Bachelor's degree in related field or an equivalent combination of education and experience.
• Four (4) years of relevant professional experience in data science, applied artificial intelligence, machine learning, business intelligence, reporting and analytics, customer or marketing analytics, statistical analysis, predictive modeling, data engineering, software or application development, or related quantitative and technical work.
• This position requires the employee to reside in Ohio. The position may be eligible for a flexible work arrangement, including remote or hybrid work, in accordance with university and unit policies. Any flexible work arrangement is subject to manager approval and may be modified or discontinued based on operational needs, position responsibilities, or performance.

Desired Qualifications (We’re committed to building a team that reflects a variety of skills and experiences and encourage you to apply even if your experience does not align perfectly)

• Advanced degree in data science, data analytics, statistics, applied mathematics, computer science, information systems, engineering, economics, business, marketing, human-computer interaction, or a related field, or additional relevant education and experience.
• Six (6) years of relevant experience.
• Experience using programming or query languages to analyze data and develop data science, machine-learning, AI, or analytical solutions.
• Experience creating predictive models or applying statistical, machine-learning, generative AI, natural language processing, or comparable methods to practical problems.
• Experience working with business partners or intended users to understand needs, translate business problems into analytical or technical work, and communicate findings or solutions to technical and nontechnical audiences.
• Experience using Python, R, SQL, or comparable languages for data analysis, predictive modeling, machine learning, AI, or application development; proficiency in Python and SQL is preferred.
• Experience with cloud data and AI platforms, preferably Azure Databricks or Microsoft Azure. Experience with Apache Spark or PySpark for distributed data processing, analytics, or machine learning is also desirable.
• Experience developing applied AI solutions, such as agents, conversational experiences, intelligent search, retrieval-augmented generation, semantic search, tool integrations, structured outputs, or multi-step workflows.
• Experience using AI-assisted or agentic development tools, such as Claude Code, GitHub Copilot, Databricks Genie Code, or comparable technologies, to develop, review, test, debug, or document code and applications.
• Experience implementing or supporting analytical, machine-learning, AI, or software solutions for business users, including application development, integration, evaluation, deployment, monitoring, documentation, training, or adoption.
• Experience with development and solution-lifecycle practices such as Git or GitLab, MLflow, APIs, versioning, code review, repeatable testing, usability and accessibility practices, experimental design, or responsible AI.
• Experience in higher education, Advancement, fundraising, alumni engagement, nonprofit development, marketing, customer or audience analytics, consulting, product development, or another complex, relationship-centered environment.

The Office of Advancement is committed to providing tools and resources for you to learn our business, proprietary databases, university-specific processes, and advancement practices.

You Need to Know

Aside from the unparalleled benefits of working for The Ohio State University and working in the vibrant, smart, enjoyable, and growing city of Columbus, Ohio, this opportunity will provide exceptional rewards that arise from working for an institution doing worldwide life-changing teaching and research.

Learn more here

Careers at Ohio State .

In accordance with the Disaster Preparedness and University State of Emergency Policy 6.17 this position has been designated as a standby position.

Additional Information: ---------------------------

To learn more about the Office of External Affairs, please visit Advancement Careers .

The budget for this position is up to $113,449.96. The offer for this position will be based on internal equity and the candidate's qualifications.

Function

Business Planning and Operations

Sub-function: Data Analytics Science

Career Band: Individual Contributor - Specialized

Career Level: S3 Senior

Location: -------------

University Square North (1031) Position Type: ------------------

Regular Scheduled Hours: --------------------

40 Shift: ----------

First Shift Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.

Thank you for your interest in positions at The Ohio State University and Wexner Medical Center. Once you have applied, the most updated information on the status of your application can be found by visiting the Candidate Home section of this site. Please view your submitted applications by logging in and reviewing your status.

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The university is an equal opportunity employer, including veterans and disability.