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Afternoon Data Analyst R Programming Jobs in Birmingham, AL

Job Title :: Data Analyst 2 Location :: Birmingham, AL 35203(Onsite) Contract :: 6-Months Skills and Responsibilities · 3-5 Years Proficient in using tools like Python, R, SQL, and data ...

Motion Industries is seeking a Business Intelligence Data Analyst who will design and develop ... developer and influencer of peers. Preferred : • Proficiency in Python, R, or other statistics ...

Bachelor's degree in Data Analytics, Information Systems, Business, Mathematics, Engineering, GIS, Computer Science, or a related field. * 0-2 years of experience in data analysis, data management ...

... Analyst I with 1-3 years of experience to support data analysis, reporting, data integration, and ... Use Python, R, SQL , and visualization tools to identify trends, patterns, and insights. * Build ...

Working knowledge of at least one major programming language (e.g., Python, C#, Java, or Scala) required. * Proficiency with statistical analysis and data visualization tools (e.g., Tableau, Power BI ...

This role utilizes various analytical and programming skills to develop BI solutions and supports ... Python, R, or other statistics platform preferred. • Professional presence with excellent ...

This role utilizes various analytical and programming skills to develop BI solutions and supports ... Python, R, or other statistics platform preferred. • Professional presence with excellent ...

Collaborate with Planning, Purchasing, Operations, and Engineering teams to ensure data integrity ... Strong analytical and problem-solving skills with the ability to interpret data and identify trends

Data Science Tutor

Birmingham, AL · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Strategy-Manager

Birmingham, AL · On-site

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Contract-to-Hire About the Opportunity This is a great opportunity for a Healthcare Data Analyst or SQL Developer looking to grow into the Epic ecosystem. The team is open to candidates who do not ...

Data Visualization Engineer I

Birmingham, AL · On-site

$107K - $128K/yr

... programming languages, and cloud data environments, and demonstrates strong analytical and problem ... R or Java * pandas * dbt * Git * Tableau * Power BI * Microsoft Excel Familiarity with: * ETL ...

Responsibilities include sourcing, cleaning, and transforming data; researching applicable methods ... Comprehensively and clearly document all modeling or analysis work that meets internal, GAAP, and ...

Proficiency in at least one programming language: * Python or * R * Hands-on experience with data wrangling, analysis, and exploration * Familiarity with a wide range of machine learning algorithms

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Afternoon Data Analyst R Programming information

See Birmingham, AL salary details

$31.9K

$77.5K

$127.5K

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

As of Jul 16, 2026, the average yearly pay for afternoon data analyst r programming in Birmingham, AL is $77,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $90,900.00 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, and why are they important?

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 the most commonly searched types of Data Analyst R Programming jobs in Birmingham, AL? The most popular types of Data Analyst R Programming jobs in Birmingham, AL are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Birmingham, AL? For Afternoon Data Analyst R Programming jobs in Birmingham, AL, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Birmingham, AL look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Birmingham, AL are:
Data Analyst 2

Data Analyst 2

4P Consulting Inc.

Birmingham, AL • On-site

Contractor

Re-posted 19 days ago


Job description

Job Title :: Data Analyst 2

Location :: Birmingham, AL 35203(Onsite)

Contract :: 6-Months

Skills and Responsibilities

· 3-5 Years Proficient in using tools like Python, R, SQL, and data visualization libraries (e.g., Matplotlib, Seaborn, Tableau) to analyze and present data insights effectively.

· Data Integration and ETL: Skilled in data extraction, transformation, and loading (ETL) processes, working with various data sources and databases to prepare data for analysis.

· Statistical Analysis: Proficiency in statistical analysis and hypothesis testing to draw

· meaningful conclusions from data, as well as the ability to apply machine learning

techniques for predictive modeling.