1

Afternoon Data Analyst R Programming Jobs in Fort Atkinson, WI

... data for analysis is preferred. Familiarity with coding languages such as R, Python, Matlab, or ... Engineering, or related field preferred. How to Apply: For the best experience completing your ...

Data Engineer (Hybrid)

Cottage Grove, WI ยท On-site

$108K - $130K/yr

As a Data Engineer, you'll play a critical role in shaping and executing Summit's data strategy ... Analyze complex datasets to identify trends, answer business questions, and support informed ...

... analytics. * Advanced proficiency with statistical software and programming languages, specifically Python and R. * Experience using and managing workflows in open-source platforms like GitHub, for ...

Affordability Analyst III

Madison, WI ยท On-site

$90K - $155K/yr

Strong proficiently in data analysis tools (e.g., SQL, Python, R, Excel) and visualization techniques/software (e.g. Power BI, Tableau) * Proven experience in developing and implementing data ...

Showing results 21-40

Afternoon Data Analyst R Programming information

See Fort Atkinson, WI salary details

$31K

$75.4K

$124.1K

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

As of Aug 19, 2026, the average yearly pay for afternoon data analyst r programming in Fort Atkinson, WI is $75,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,000.00 and $88,500.00 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 are popular job titles related to Afternoon Data Analyst R Programming jobs in Fort Atkinson, WI?

For Afternoon Data Analyst R Programming jobs in Fort Atkinson, WI, the most frequently searched job titles are:

What job categories do people searching Afternoon Data Analyst R Programming jobs in Fort Atkinson, WI look for?

The top searched job categories for Afternoon Data Analyst R Programming jobs in Fort Atkinson, WI are:

What cities near Fort Atkinson, WI are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Fort Atkinson, WI with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in Fort Atkinson, WI as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $75,415 per year, or $36.3 per hour.

Clinical Research Data Specialist

Wisconsin

Madison, WI โ€ข On-site

$62K/yr

Full-time

Retirement, PTO

Posted 13 days ago


Job description

Current Employees: If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.Job Category:Academic StaffEmployment Type:RegularJob Profile:Data Engineer IJob Summary:

The Department of Orthopedics and Rehabilitation is seeking a Clinical Research Data Specialist to assist in database development and management of multiple clinical and research databases. This position will primarily support clinical departmental databases and help manage centralizing data in an efficient and accurate manner, as well as assist with preparing datasets for analysis. This will include development of standard operating procedures for all aspects of data entry, quality assessments, and exporting for analysis. Additionally, the position will support creating, maintaining, and analyzing research databases for prospective research studies. This position will work closely with the Badger Athletic Performance program, patient reported outcome data, and data extracted from the electronic medical record.

A successful candidate will have experience working with large clinical datasets in a research setting. Demonstrated experience with data management via software including REDCap and Excel are strongly preferred. Familiarity with the research process including data collection and preparing data for analysis is preferred. Familiarity with coding languages such as R, Python, Matlab, or others is helpful but not required.

  • This position requires work to be completed onsite, at a designated campus work location.

Key Job Responsibilities:
  • Develops, constructs, tests, and maintains architectures for large-scale data management and analysis
  • Serves as an institutional subject matter expert and liaison to key internal and external stakeholders regarding automated data management and analysis at scale for research and represents the interests of large-scale data management and analysis for research
  • Selects appropriate technologies and optimizes pipelines for performance
  • Organizes both data preparation and analysis steps into reproducible pipelines that can process similar data sets automatically
  • Implements data analysis steps in collaboration with data scientists, statisticians, and/or other researchers and may use technologies that support data at scale
  • Prepares data sets for current and future analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources and may use technologies that support data at scale
  • May supervise the data-to-day activities of staff and resolves routine personnel issues
Department:

School of Medicine and Public Health, Department of Orthopedics & Rehabilitation, Sports Medicine

TheDepartment of Orthopedics and Rehabilitationis committed to conducting cutting edge research, training the next generation of leaders and providing world-class patient care for both adults and pediatric patients. The Department embraces both independent and collaborative work-styles. Our general approach is to empower individuals to work independently through thorough and hands-on training and onboarding, while also having regular meetings with collaborators and support staff within the department to foster a strong team environment.

Compensation:

The starting salary for the position is $62,000 annually; but is negotiable based on experience and qualifications.

Employees in this position can expect to receive benefits such as generous vacation, holidays, and sick leave; competitive insurances and savings accounts; retirement benefits. For more information, refer to the campus benefits webpage and the SMPH Faculty /Academic Staff Benefits Flyer 2026

Preferred Qualifications:
  • Experience building REDCap databases

  • Experience working with data obtained from clinical settings

Education:

Bachelor's degree preferred minimum.

Applicants with Master's Degree are highly preferred and given first consideration; focus in Bioinformatics, Clinical Informatics, Data Science, Data Engineering, or related field preferred.

How to Apply:

For the best experience completing your application, we recommend using Chrome or Firefox as your web browser.

To apply for this position, select either "I am a current employee" or "I am not a current employee" under Apply Now. You will then be prompted to upload your application materials.

Important: The application has only one attachment field. Upload the following documents in that field, either as a single combined file or as multiple files in the same upload area. Failure to submit the required documents will result in no longer being considered for the position.
Cover letter required
Resume required

Your cover letter should address how your training and experience aligns with the preferred qualifications listed above and how this position aligns with your long-term career goals. Application reviewers will rely on these written materials to determine which applicants move forward in the process. References will be requested from final candidates. All applicants will be notified once the search concludes and a candidate is selected

University sponsorship is not available for this position, including transfers of sponsorship and TN visas.The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment.If you are selected for this position you must provide proof of work authorization and eligibility to work.

Contact Information:

Mikel Joachim, joachim@ortho.wisc.edu, 608-890-4261

Relay Access (WTRS): 7-1-1. See RELAY_SERVICE for further information.

Institutional Statement on Diversity:

Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.
The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world.


The University of Wisconsin-Madison is an Equal OpportunityEmployer.

Qualified applicants will receive consideration for employment without regard to, including but not limited to, race, color, religion, sex, sexual orientation, national origin, age, pregnancy, disability, or status as a protected veteran and other bases as defined by federal regulations and UW System policies. We promote excellence by acknowledging skills and expertise from all backgroundsand encourage all qualified individuals to apply. For more information regarding applicant and employee rights and to view federal and state required postings, visit the Human Resources Workplace Poster website.


To request a disability or pregnancy-related accommodationfor any step in the hiring process (e.g., application, interview, pre-employment testing, etc.), please contact the Divisional Disability Representative (DDR)in the division you are applying to.Please make your request as soon as possible to help the university respond most effectively to you.


Employment may require a criminal background check. It may also require your references to answer questions regarding misconduct, including sexual violence and sexual harassment.
The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the successful candidate will be released. See Wis. Stat. sec. 19.36(7).
The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. UW-Madison will provide a paper copy upon request; please contact the University of Wisconsin Police Department.