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Afternoon Data Analyst R Programming Jobs in Kentucky

$138 - $167/hr

As a Data Science Analyst/Engineer join the the Data Engineering Team responsible for integrating new Data Stores and building the Metadata Application Profile (MAP) that aligns attributes from ...

New

$180 - $240/hr

You'll partner closely with product managers and engineers as a trusted analytical resource, while contributing to a culture of data excellence within our centralized Data & Analytics organization.

New

$69K - $87K/yr

As a Senior Business Data Analyst, you will serve as a senior analytics partner and business intelligence subject matter expert, helping offices across the institution transform complex data into ...

Data Science Tutor

Lexington, KY ยท 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 ...

$120 - $180/hr

Our platform combines Rust-speed performance with elegant tools that developers love to use ... About the role We are hiring a Senior Data Analyst to build the trusted data foundation Chalk uses ...

Data Science Tutor

Louisville, KY ยท 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 ...

$140 - $149/hr

A Master's degree is preferred (e.g., MBA, MS in Engineering, or Data Science). * Minimum of 5 ... Advanced skills in data visualization and analytics tools, including Tableau, Power BI, Python, SQL ...

New

$90 - $100/hr

... R programming to lead and support clinical and public health research projects. This role involves providing statistical leadership in study design, EHR data management and analysis, manuscript ...

New

Showing results 41-60

Afternoon Data Analyst R Programming information

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 the most commonly searched types of Data Analyst R Programming jobs in Kentucky?

The most popular types of Data Analyst R Programming jobs in Kentucky are:

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

The top searched job categories for Afternoon Data Analyst R Programming jobs in Kentucky are:

What cities in Kentucky are hiring for Afternoon Data Analyst R Programming jobs?

Cities in Kentucky with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in Kentucky as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Principal Statistical Programmer

Neshent Technologies

Latonia, KY โ€ข On-site

Full-time

Posted 5 days ago


Job description

We are seeking an experienced Principal Statistical Programmer to lead statistical programming activities for clinical development programs. The ideal candidate will have strong expertise in SAS programming, CDISC standards, ADaM datasets, TLF development, regulatory submissions, and clinical trial data analysis. This role will provide technical leadership, mentor statistical programmers, and collaborate with cross-functional clinical teams.

Required Skills & Experience
  • Experience leading a team of statistical programmers supporting clinical development programs.
  • Strong proficiency in SAS programming for developing and validating:
    • ADaM datasets
    • Tables, Listings, and Figures (TLFs)
    • Statistical analyses
  • Good knowledge of R programming and other statistical programming languages preferred.
  • Strong understanding of SAS programming concepts and the clinical study lifecycle.
  • In-depth knowledge of CDISC standards (SDTM/ADaM) and regulatory requirements.
  • Experience supporting regulatory filings and submission documentation.
  • Experience working in therapeutic areas such as Oncology, Immunology, Neuroscience, or similar domains.
  • Strong communication and collaboration skills with cross-functional teams.
  • Ability to estimate project programming efforts and manage competing priorities.
Roles and Responsibilities
  • Lead statistical programming activities for assigned compounds, indications, or therapeutic areas.
  • Manage and mentor statistical programmers, analysts, and senior analysts.
  • Plan resources, track deliverables, and ensure timely completion of programming activities.
  • Develop and oversee SAS programs for ADaM dataset creation following CDISC standards.
  • Develop and review SAS programs for Tables, Listings, and Figures (TLFs).
  • Ensure consistency and quality of ADaM datasets across individual studies and integrated analyses.
  • Support regulatory submissions by preparing documentation such as reviewer guides and data definition documents.
  • Develop standard SAS macros, programming standards, and operating procedures.
  • Ensure compliance with quality processes and clinical programming best practices.
  • Collaborate with Statisticians, Clinical Data Management, Medical Writing, Regulatory Publishing, and Clinical Operations teams.
Preferred Qualifications
  • Experience in pharmaceutical, biotechnology, or clinical research environments.
  • Strong knowledge of clinical trial programming and regulatory submission processes.
  • Excellent leadership, problem-solving, and organizational skills.
  • Ability to work effectively in a dynamic, deadline-driven environment.