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Afternoon Data Analyst R Programming Jobs in Ashland, KY

Danaher

Digital Analyst Internships

Huntington, WV

$83K - $98K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Danaher

Digital Analyst Internships

Huntington, WV · On-site

$83K - $98K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

FocusKPI

Marketing Operations Analyst

Huntington, WV · On-site

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate data from various sources into the customer data platform (CDP) for comprehensive analysis.

Stratus Team LLC

Project Operations Analyst

Huntington, WV · On-site

$95K - $125K/yr

About Stratus Stratus ® is an integrated, multi-disciplinary engineering, architecture, interior ... Monitor project portfolio performance including margin variance, unbilled, and A/R, and partner ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Ashland, KY

Afternoon Data Analyst R Programming information

See Ashland, KY salary details

$29.8K

$72.5K

$119.4K

How much do afternoon data analyst r programming jobs pay per year?

As of Sep 9, 2026, the average yearly pay for afternoon data analyst r programming in Ashland, KY is $72,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,900.00 and $85,100.00 per year, depending on experience, location, and employer.

What is an afternoon data analyst r programming?

An Afternoon Data Analyst specializing in R Programming is a data professional who primarily works afternoon shifts and uses the R programming language to analyze, interpret, and visualize data. Their responsibilities typically include cleaning data, performing statistical analyses, and generating reports to support business decisions. They may work across various industries, collaborating with teams to provide insights and automate data processes using R. Afternoon shifts can be ideal for organizations that operate globally or require data support outside standard business hours. Proficiency in R, statistical techniques, and data visualization tools are essential skills for this role.

What are the key skills and qualifications needed to thrive as an afternoon data analyst specializing in R programming?

To thrive as an Afternoon Data Analyst specializing in R Programming, you need a strong background in statistics, data analysis, and proficiency with R, often supported by a degree in a quantitative field. Experience with data visualization tools, R packages (like tidyverse), and familiarity with databases or version control systems (such as Git) is typically required. Critical thinking, attention to detail, and effective communication are essential soft skills for interpreting results and presenting insights to stakeholders. These skills ensure accurate data-driven decisions, efficient workflow, and the ability to translate complex data into actionable business strategies.

What are some common challenges faced by afternoon data analysts working with R programming, and how can they be addressed?

Afternoon Data Analysts using R Programming often encounter challenges such as handling large datasets efficiently, ensuring code reproducibility, and collaborating with team members across different shifts. To address these, it's helpful to utilize R packages designed for big data (like data.table or dplyr), maintain clear and well-documented scripts, and use version control systems like Git for seamless collaboration. Regular communication with team members during shift handovers and leveraging collaborative tools can also enhance workflow and reduce misunderstandings.

What is the difference between Afternoon Data Analyst R Programming vs Morning Data Analyst R Programming?

AspectAfternoon Data Analyst R ProgrammingMorning Data Analyst R Programming
Required CredentialsBachelor's in Data Science, Statistics, or related field; R programming skillsBachelor's in Data Science, Statistics, or related field; R programming skills
Work EnvironmentTypically in office settings, working during afternoon hoursOffice environment, working during morning hours
Employer & Industry UsageUsed in industries with shift-based operations like finance, healthcareCommon in similar industries, often with flexible scheduling
Search & Comparison IntentPeople comparing different shift roles or schedules in data analysisSimilar search intent focusing on shift timing differences

The main difference between Afternoon Data Analyst R Programming and Morning Data Analyst R Programming lies in their work hours. Both roles require similar skills, credentials, and are used in comparable industries. The choice depends on personal schedule preferences and employer shift structures.

What cities near Ashland, KY are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Ashland, KY with the most Afternoon Data Analyst R Programming job openings:

Afternoon Data Analyst R Programming jobs near you
Infographic showing various Afternoon Data Analyst R Programming job openings in Ashland, KY as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $72,530 per year, or $34.9 per hour.

Institutional Research Data & AI Solutions Sr Analyst

Huntington, WV • On-site

Marshall University
Colleges, Universities, and Professional Schools • 1 - 5K employees
Learn more about Marshall Universityexternal

$112K - $113K/yr

Full-time

Posted 23 days ago

Marshall University rating

6.1

Company rating: 6.1 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

561st of 633 rated colleges and universities

Job description

Position Information
Position Title Institutional Research Data & AI Solutions Sr Analyst Banner Position Number 000970 E-Class NC - Nonclassified - .53 or > Department Institutional Research & Planning - MU2040 Job Description
Marshall University is seeking an Institutional Research Data & AI Solutions Sr Analyst to join the Office of Institutional Research and Planning. Reporting through Institutional Research and Planning, this position combines traditional institutional research, data analysis, and decision support with the design and development of artificial intelligence solutions that improve access to information, and institutional decision-making to support university operations
The successful candidate will analyze institutional data, support federal, state, and university reporting requirements, and conduct studies related to enrollment, retention, student success, academic programs, personnel, and institutional effectiveness. The position will also develop responsible AI-enabled applications, agents, automations, and analytical tools that help university employees locate information, interpret and analyze data and make informed decisions.
Working collaboratively with Institutional Research and Planning, Information Technology, academic and administrative units, and university data stewards, the position will translate institutional data into practical analytical and AI solutions. The employee will help ensure that AI solutions are accurate, secure, appropriately governed, technically sustainable, and aligned with university policies, technology standards, data standards, and strategic priorities.
Key Responsibilities

1. Institutional Research and Decision Support

  • Collect, analyze, interpret, and communicate institutional data to support university planning, policy development, operational improvement, and strategic decision-making.
  • Conduct analyses related to enrollment, retention, persistence, graduation, student success, academic programs, workforce trends, financial planning, and institutional performance.
  • Prepare reports, presentations, visualizations, and written summaries that translate complex findings into clear and actionable information.
  • Respond to ad hoc data and research requests from university administrators, academic units, committees, and other institutional stakeholders.
  • Assist with institutional studies, benchmarking projects, surveys, program evaluations, and assessment activities.
  • Apply appropriate statistical, analytical, and research methods to evaluate institutional questions and measure outcomes.

2. AI Solutions Development
  • Design, develop, test, and maintain AI-enabled solutions including agents, assistants, and workflow solutions that address institutional research, data, analytical, and administrative needs.
  • Lead development when the principal purpose of a solution is institutional data analysis, data interpretation, reporting, predictive analytics, or data-informed decision support.
  • Collaborate with Information Technology on AI and automation initiatives that require enterprise applications, systems integration, infrastructure, identity management, cybersecurity, or operational workflow development.
  • Provide institutional data knowledge, analytical logic, data definitions, and governance expertise to solutions led by Information Technology or other university units.
  • Create retrieval-augmented generation solutions that allow authorized users to obtain answers from trusted university documents, policies, data definitions, analytical resources, and institutional information, including the university's data warehouse or other sources used in AI solutions.
  • Develop AI-supported workflows for information retrieval, document analysis, data interpretation, classification, summarization, routing, and other appropriate university uses.
  • Contribute institutional data expertise to enterprise applications, AI tools, and automations led by Information Technology when those solutions require university data, data definitions, analytical logic, or reporting capabilities.
  • Integrate AI solutions with approved university systems, data platforms, reporting environments, and knowledge repositories in coordination with Information Technology.
  • Monitor AI solutions for accuracy, reliability, usability, security, and continued alignment with institutional and technical requirements.
  • Maintain technical documentation, user instructions, testing records, ownership information, change logs, and support procedures for developed solutions.

3. Data Analysis, Programming, and Automation
  • Query, transform, validate, and analyze data from enterprise systems and relational databases using SQL and other analytical tools.
  • Use Python or comparable programming languages to support data preparation, statistical analysis, predictive modeling, automation, and AI application development.
  • Develop automated processes that improve the efficiency, consistency, and reproducibility of institutional reporting and analysis.
  • Work with structured and unstructured data from multiple institutional sources.
  • Collaborate with business intelligence and data professionals to use approved data models, semantic layers, data warehouses, and institutional reporting resources.
  • Assist with the development and validation of predictive, forecasting, or classification models related to enrollment, retention, student outcomes, and institutional operations.

4. Reporting and Institutional Research Operations
  • Support the collection, validation, and submission of information required for federal, state, accreditation, and institutional reporting such as IPEDS, state higher education reporting, institutional data publications, and external surveys.
  • Apply established definitions, reporting standards, and quality-assurance procedures to ensure the accuracy and consistency of reported information.
  • Work collaboratively with the Institutional Research and Planning team to coordinate and complete institutional research projects.

5. Consultation, Training, and Collaboration
  • Meet with university stakeholders to identify research questions, operational challenges, information needs, and potential AI use cases.
  • Translate business and institutional requirements into clear analytical or technical solution designs.
  • Provide demonstrations, training, documentation, and support to university employees using developed tools.
  • Promote data literacy, responsible AI use, and evidence-based decision-making across the institution.
  • Collaborate effectively with technical and nontechnical employees in academic and administrative areas.
  • Remain current with developments in institutional research, higher education analytics, artificial intelligence, data governance, and emerging technology.
  • Perform other duties as assigned.
Salary Range $52,105 - $67,736 Salary Type Salary Time Type Full-Time Work Location MU - Marshall University
Qualifications
Must be able to perform all essential job duties as outlined in the job description.
Required Qualifications
Education
Bachelor's degree in data science, computer science, information systems, statistics, mathematics, economics, business analytics, educational research, social science, or another quantitative, analytical, or technical field.
Experience
  • 1 to 2 years of experience conducting data analysis, institutional research, business intelligence, applied research, software development, or a closely related function at a university.
  • Demonstrated proficiency using SQL to query, transform, and analyze data from relational databases.
  • Experience using Python, R, JavaScript, or another programming language for data analysis, automation, application development, or statistical computing.
  • Demonstrated experience with generative AI tools, automated workflows, analytical applications, or comparable technology solutions.
  • Experience assessing and interpreting data and communicating validated analytical findings to technical and nontechnical audiences.
  • Experience developing dashboards or analytical visualizations in Power BI or a comparable business intelligence platform.
  • Strong written communication, consultation, presentation, and problem-solving skills.
Preferred Qualifications
Education
Master's degree in data science, computer science, information systems, statistics, business analytics, educational research, higher education, public administration, or a related field.

Experience
  • 2-3 years of experience working in institutional research, institutional effectiveness, higher education analytics, or a higher education administrative environment.
  • Experience analyzing solutions using Microsoft Copilot Studio, Azure AI, Azure OpenAI, Power Platform, or comparable AI and low-code platforms.
  • Experience analyzing retrieval-augmented generation applications, AI agents, chat interfaces, or solutions that use large language models.
  • Experience integrating applications through APIs, data connectors, or automated workflows.
  • Experience with prompt design, AI evaluation, grounding methods, model testing, and human-in-the-loop review.
  • Experience with predictive analytics, machine learning, forecasting, natural language processing, or statistical modeling.
Posting Detail Information
Posting Number MU1281E Open Date 08/17/2026 Close Date Open Until Filled Yes Special Instructions Summary

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