ZipRecruiter

Log In

1

Afternoon Data Analyst R Programming Jobs in Knightdale, NC

CYNET SYSTEMS

Business Data Analyst

Cary, NC · On-site

$60 - $65/hr

Basic knowledge of writing syntaxes and a solid background in programming languages. * Strong ... Data Mapping. * UML. * Data Flow Modeling. * Workflow Analysis. * Functional Decomposition.

S3

Data Analyst II

Raleigh, NC

Data Analyst II Location: Charlotte, NC OR Raleigh, NC (Hybrid) Duration: 2+ Year Contract Overview ... Experience with Python programming language * Document warehouses to support cross training of co ...

Redhat

Principal Data Analyst

Raleigh, NC · On-site +1

$125K - $180K/yr

... engineers to implement data solutions and pipelines integrating data between platforms. #LI-DNI The salary range for this position is $125,653 - $180,000/year. Actual offer will be based on your ...

New

Segment (Twilio)

Senior AI FinOps Data Analyst

Raleigh, NC · On-site

$88.51 - $141.63/hr

The Senior FinOps Data Analyst sits at the intersection of Cloud Infrastructure, Corporate Finance, and AI Engineering. This is not an administrative or passive reporting role; it requires an AI ...

New

previous pagenext page

Showing results 21-40

All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Knightdale, NC

Afternoon Data Analyst R Programming information

See Knightdale, NC salary details

$30.6K

$74.4K

$122.4K

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

As of Aug 20, 2026, the average yearly pay for afternoon data analyst r programming in Knightdale, NC is $74,395.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,300.00 and $87,300.00 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 job categories do people searching Afternoon Data Analyst R Programming jobs in Knightdale, NC look for?

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

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

Cities near Knightdale, NC 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 Knightdale, NC as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $74,395 per year, or $35.8 per hour.

Statistical Programmer / Clinical Data Architect

Volto USA

Raleigh, NC • On-site

Contractor

Re-posted 18 days ago

Job description

Job Description: Local to Raleigh, NC  Only!
Role Overview
We are seeking a highly experienced Senior Statistical Programmer / Clinical Data Architect with 15+ years of expertise in clinical data programming, CDISC standards, and cloud-based analytics platforms. The ideal candidate will lead end-to-end clinical data workflows, regulatory submissions, and modern data platform transformations in GxP-regulated environments.
This role requires strong domain expertise in SDTM, ADaM, regulatory submissions, and SAS/Python/R programming, combined with experience in cloud platforms (AWS/Azure) and clinical data modernization initiatives.
________________________________________
Key Responsibilities
Clinical Data Programming & Regulatory Submissions
•       Design, develop, and validate SDTM and ADaM datasets in compliance with CDISC standards
•       Lead generation of define.xml, aCRF/eCRF annotations, and submission-ready deliverables
•       Develop and optimize automated submission pipelines for FDA and global regulatory authorities
•       Ensure compliance with GxP, 21 CFR Part 11, HIPAA, and ICH E6 guidelines
Data Engineering & Automation
•       Architect and implement end-to-end clinical data pipelines using SAS, Python, and R
•       Develop reusable SAS macro libraries and automation frameworks
•       Build scalable data pipelines including modern formats (JSON/XPT alternatives)
•       Drive migration from legacy systems to modern data architectures
Cloud & Platform Engineering
•       Lead implementation and optimization of SAS Viya platforms on AWS/Azure
•       Manage cloud infrastructure components (EKS, EC2, EFS, FSx, Databricks, etc.)
•       Implement FinOps practices for cost governance and optimization
•       Evaluate and onboard next-gen analytics platforms (e.g., Databricks)
Leadership & Stakeholder Management
•       Lead cross-functional teams across US, UK, and offshore locations
•       Collaborate with clinical, statistical, regulatory, and IT stakeholders
•       Drive Agile delivery and sprint planning for data and platform initiatives
•       Manage vendor relationships, tool selection, and licensing strategies
Compliance & Governance
•       Ensure adherence to regulatory and audit requirements (FDA, OCC, SOX, Basel III as applicable)
•       Maintain audit-ready documentation and validation processes
•       Implement data governance, traceability, and reproducibility standards
________________________________________
Required Qualifications
•       Bachelor’s or Master’s degree in Computer Science, Statistics, Life Sciences, or related field
•       15+ years of experience in statistical programming and clinical data management
•       Strong expertise in:
o       SAS (Base, Macro, SQL, ODS, STAT, Graph)
o       CDISC standards (SDTM, ADaM, define.xml)
o       Regulatory submissions (FDA, global agencies)
•       Hands-on experience with:
o       Python (Pandas) and/or R (admiral, Shiny)
o       Cloud platforms (AWS/Azure)
•       Strong understanding of GxP and clinical compliance frameworks
________________________________________
Preferred Qualifications
•       Experience with SAS Viya architecture and administration
•       Familiarity with Databricks, DBT, or modern data engineering tools
•       Knowledge of CI/CD tools (Jenkins, Git)
•       Experience in financial/regulatory environments (Basel III, CCAR, OCC) is a plus
•       AWS or cloud certifications
________________________________________
Key Skills
•       Clinical Data Standards: SDTM, ADaM, CDISC
•       Programming: SAS, Python, R, SQL
•       Cloud: AWS, Azure
•       Tools: Pinnacle 21, Git, Jenkins, Power BI, Grafana
•       Methodologies: Agile, DevOps, Data Governance