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Afternoon Data Analyst R Programming Jobs (NOW HIRING)

Collaborate with subject matter experts, internal/external stakeholders, software programmers, and ... Significant experience with data analysis software such as Python, R, or Matlab. * Experience ...

Advanced experience with a statistical programming language (Python or R) for in-depth data analysis, statistical modeling, and visualization (using libraries such as Pandas, NumPy, Matplotlib ...

Data Scientist under general supervision will perform data engineering, data modeling and model ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

Data Scientist under general supervision will perform data engineering, data modeling and model ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

Data Analyst

Dallas, TX · Remote

$23.50 - $30.50/hr

... within the engineering or construction industry. * Proven experience with data visualization tools (e.g., Tableau, Power BI) and statistical analysis software (e.g., R, Python, or similar)

Data Scientist under general supervision will perform data engineering, data modeling and model ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

Data Scientist under general supervision will perform data engineering, data modeling and model ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

... SQL, etc), programming (XML, Javascript, or ETL frameworks) • Knowledge of statistics and ... SQL, python, r, excel, tableau, power bi,was, spss, data visualization, data mining, machine ...

... programming (XML, Javascript, or ETL frameworks) Knowledge of statistics and experience using ... SQL, python, r, excel, tableau, power bi,was, spss, data visualization, data mining, machine ...

... programming concepts Experience with statistical tools and concepts (R, SPSS, SAS) Preferred skill set: Experience with Oracle/Exadata, Teradata, AWS Redshift/Hadoop, Splice open source data ...

Data Analyst

San Francisco, CA · Remote

$1.0K - $1.2K/mo

Proficient in programming languages such as Python or R, with the ability to manipulate and analyze data efficiently. * Adept at working with large datasets, utilizing statistical techniques to ...

Working knowledge of programming languages like Python or R for data analysis, automation, and statistical modeling * Experience handling and analyzing large, complex datasets, with an understanding ...

Data Analyst

Springfield, VA · On-site

$110K - $150K/yr

Data analysis competency with mathematical programming languages (i.e., MATLAB, Python, R, etc.) or equivalent with the ability to produce charts and tables. * Ability to exercise independent ...

Data Analyst

Springfield, VA · On-site

$110K - $150K/yr

Data analysis competency with mathematical programming languages (i.e., MATLAB, Python, R, etc.) or equivalent with the ability to produce charts and tables. * Ability to exercise independent ...

R Programming SQL Data Analysis Specific Accountabilities/Essential Functions of Position Conceptualize, design and support the implementation of analytics and reports utilizing a variety of data ...

Collaborate closely with engineering teams on data sourcing, transformations, pipeline optimization ... Proficiency in data analysis, data wrangling, and automation using Python and/or R. * Experience ...

Showing results 41-60

Afternoon Data Analyst R Programming information

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$34K

$82.6K

$136K

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

As of Aug 5, 2026, the average yearly pay for afternoon data analyst r programming in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 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 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 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.
More about Afternoon Data Analyst R Programming jobs
What cities are hiring for Afternoon Data Analyst R Programming jobs? Cities with the most Afternoon Data Analyst R Programming job openings:
What are the most commonly searched types of Data Analyst R Programming jobs? The most popular types of Data Analyst R Programming jobs are:
What states have the most Afternoon Data Analyst R Programming jobs? States with the most job openings for Afternoon Data Analyst R Programming jobs include:
What job categories do people searching Afternoon Data Analyst R Programming jobs look for? The top searched job categories for Afternoon Data Analyst R Programming jobs are:
Infographic showing various Afternoon Data Analyst R Programming job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 53% Full Time, 37% Part Time, 1% Temporary, 1% Contract, and 7% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Full-time

Re-posted 10 days ago


Job description

Company Description

The activities for this position are centered on developing solutions through data science techniques required. In this role you will perform critical functions such as:

  • Identify potential applications fro data science techniques
  • Assist management in setting priorities for near-term projects
  • Drive the collection of new data and the manipulation/refinement of existing data sources
  • Analyze data using data science and/or statistical methods
  • Collaborate with subject matter experts, internal/external stakeholders, software programmers, and customers to develop tools that meet specifications
  • Issue reports detailing tool development (including unsuccessful approaches), quality assurance actions performed, final results, etc.

As a member of the Data Methods team, you will also have the opportunity to train others (all levels of design, architecture, and management), collaborate with external experts, and attend conferences/training sessions.

Job Requirements

Senior:

  • BS degree in Admin or Bachelor's degree in a design related field from an accredited college, university & companies and a minimum of 1+ years relevant experience; or
  • MS degree in engineering or Master's degree in a Data analyst related field from an accredited college or university and a minimum of four years relevant experience.

Principal:

  • BS degree in engineering or Bachelor's degree in a science related field from an accredited college or university and a minimum of nine years relevant experience; or
  • MS degree in engineering or Master's degree in a science related field from an accredited college or university and a minimum of seven years relevant experience

Job Preferred Skills

  • Significant experience with data analysis software such as Python, R, or Matlab.
  • Experience solving analytical problems using quantitative approaches.
  • Experience with hypothesis testing - the ability to develop hypotheses and test them through carefully conducted experiments.
  • MS or PhD in Aministrative related field from an accredited college or university.
Additional Information

All your information will be kept confidential according to EEO guidelines.