1

Afternoon Data Analyst R Programming Jobs in Clayton, NC

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 ...

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 ...

... engineers. Responsibilities : • Conduct comprehensive data analysis, create data mappings, develop dashboards, and ensure data quality and integrity • Leverage Spark SQL within Databricks to ...

Showing results 21-40

Afternoon Data Analyst R Programming information

See Clayton, NC salary details

$28.9K

$70.3K

$115.7K

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

As of Sep 11, 2026, the average yearly pay for afternoon data analyst r programming in Clayton, NC is $70,289.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,200.00 and $82,500.00 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 Clayton, NC?

For Afternoon Data Analyst R Programming jobs in Clayton, NC, the most frequently searched job titles are:

What job categories do people searching Afternoon Data Analyst R Programming jobs in Clayton, NC look for?

The top searched job categories for Afternoon Data Analyst R Programming jobs in Clayton, NC are:

What cities near Clayton, NC are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Clayton, NC with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in Clayton, NC as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $70,289 per year, or $33.8 per hour.

Senior Enterprise Data Analyst

Raleigh, NC • On-site

$83K - $105K/yr

Full-time

Re-posted 11 days ago


First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz


Job description

Overview

This role is part of the Enterprise Data organization and is primarily focused on the overarching governance and architecture of all data across the enterprise.

This position leads Bank initiatives that improve enterprise data quality, governance, reporting, and analytics at an advanced level of ability and technical expertise. Drives positive change across the Bank through technical innovation and continuous improvement initiatives, as well as through cross-functional partnership with other business units. Creates and maintains technical documentation related to enterprise data, including centralized critical business reports. Provides expert consultation to team members, the Information Technology department, the Bank's Data Council, and other stakeholders on strategies that achieve data management goals. May provide leadership to less experienced consultants in the work group.


Responsibilities & Qualifications

Duties & Responsibilities:
Data Enhancement - Leads the implementation of enhancements for the quality, management, and storage of enterprise data. Executes initiatives that improve profiling, exception reporting, and issue resolution as well as general fixes for the Enterprise Data Warehouse. Builds dashboards to modernize analytics and assists management with special data projects.
Business Support - Enforces data policies and procedures across the enterprise. Encourages discussion and feedback from associates in order to identify areas of improvement within data management capabilities. Completes month-end validations on reporting data to ensure the quality and completeness of data prior to business use. May assist in training or mentoring less experienced consultants in the work group.
Business Strategy - Facilitates strategies that develop the Bank’s data management capabilities. Assists management in creating and implementing a strategic road to achieve planned objectives. Works cross-functionally to mature department presence within Bank business units. Maintains a strong knowledge of current and emerging technologies or trends impacting the financial service industry.
Documentation - Creates and maintains technical documentation for the Enterprise Data Warehouse, which includes source-to-target mappings, data dictionaries, and other related materials. Identifies and creates centralized business critical reports.


Position Specific Skills:
Understanding of data warehousing and transformation methods, lineage documentation, and ETL processes
Knowledge of data spreadsheets and databases
Understanding of Base SAS programming, SAS Enterprise Guide, Cognos, or related programs
Ability to write SAS programming language


Qualifications:

Bachelor's Degree and 6 years of experience in Data Management, Data Analytics OR High School Diploma or GED and 10 years of experience in Data Management, Data Analytics

Preferred Skills: 

  • Understanding of data warehousing and transformation as well as extract, transform, and load processes, Knowledge of technologies and trends impacting the financial service and insurance industry.
  • Experience in Banking, Regulatory, Data Warehouse/Data Lakes, AWS/ Snowflake
  • Proven track record of leading agile data product delivery across cross-functional teams using agile frameworks such as Scrum, SAFe, or Kanban
  • Understanding of data warehousing and transformation methods, lineage documentation, and ETL processes, Knowledge of data spreadsheets and databases.
  • Advanced proficiency in writing complex SQL queries to perform data analysis on the complex data sets.
  • Ability to convert complex technical findings into clear, actionable narratives for both technical and non-technical stakeholders.
  • Ability to create dashboards using the tools Tableau and Power BI for reporting analysis.

#LI-XG1


Additional Information

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

What First Citizens Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom