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Afternoon Data Analyst R Programming Jobs in Warminster, PA

Judge Group, Inc.

Data Analyst

Bridgeport, PA · On-site

$70K - $85K/yr

Data Analyst (Power BI/SQL) Location: Conshohocken, PA Salary: $70,000 - $85,000 Overview We are ... Experience with version control tools (e.g., Azure DevOps Git) * Exposure to data governance ...

vTech Solution

Data Analyst

Trenton, NJ · On-site

Python Programming (Data/Automation) * Code Review & Interpretation * Data Analysis & Profiling * Automated Scripting for Ticket Resolution * Excellent Communication Skills Desired Skills: * Cloud ...

CNCSINFOTECH LLC

Data Analyst

Philadelphia, PA

The Analyst will act as a liaison between various Data and Engineering stakeholders to develop automated solutions to analyze, correlate and report data and insights to stabilize and scale our self ...

The Hartford

Investment Data Analyst

Wayne, PA

$70K - $90K/yr

Experience working with structured data using a modern scripting language, preferably R, Python, SQL or SAS. Compensation The listed annualized base pay range is primarily based on analysis of ...

The Hartford

Investment Data Analyst

Wayne, PA

$70K - $90K/yr

Experience working with structured data using a modern scripting language, preferably R, Python, SQL or SAS. Compensation The listed annualized base pay range is primarily based on analysis of ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Warminster, PA

Afternoon Data Analyst R Programming information

See Warminster, PA salary details

$33.9K

$82.3K

$135.4K

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

As of Sep 13, 2026, the average yearly pay for afternoon data analyst r programming in Warminster, PA is $82,296.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,200.00 and $96,600.00 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 cities near Warminster, PA are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Warminster, PA 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 Warminster, PA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $82,296 per year, or $39.6 per hour.

Actuarial Data Science Analyst (Insurance Hybrid role)

Philadelphia, PA • On-site

PA Compensation Rating Bureau.
See more jobs at PA Compensation Rating Bureau.external

Full-time

Re-posted 7 days ago

Job description

Job Summary:

This position supports actuarial research, business intelligence, and data analytics initiatives through statistical analysis, data engineering, and analytical model development. The employee is responsible for designing and maintaining data pipelines, performing actuarial and statistical analyses, developing analytical tools and dashboards, and communicating research findings and recommendations to technical and non-technical audiences.

The position works with large datasets using programming languages such as Python and R, SQL, and Snowflake to automate processes, conduct research, and support strategic business decisions. Responsibilities include developing reports and visualizations, evaluating emerging analytical methods, and participating in multiple concurrent projects, including research studies, data integration, predictive analytics, and business intelligence initiatives.

Essential Responsibilities:

  • Responsible for statistical analyses, actuarial and/or research models
  • Design and maintain data pipelines, analytical models, and automated processes using Python, R, SQL, Snowflake, or other programming languages.
  • Extract, validate, and analyze data from multiple sources to support research and business initiatives.
  • Drawing inferences, developing reports, and presenting analysis and recommendations to technical and non-technical audiences.
  • Participates in multiple research, business intelligence, and data analytics projects simultaneously

Requirements:

 Education: Bachelor’s Degree – B.A. / B.S. Mathematics, Statistics, Economics or Computer Science strongly preferred. A degree in Actuarial Science or a Masters in Data Science related field a plus. 

 Experience: 3 to 6 years experience in related field. 

Skills Required: Strong organizational, communication, written, and analytical skills with the ability to work independently and manage multiple priorities. Programming proficiency in Python and R is a core requirement, including experience with data manipulation, statistical analysis, and process automation. Experience with SQL, Snowflake, and advanced Excel is required. Experience with business intelligence platforms such as Pyramid, Power BI, or Tableau is preferred. The candidate must communicate effectively with all levels of personnel and external contacts.

Preferred Qualifications

  • Actuarial background or experience in the property & casualty insurance industry is a plus.

 Work Hours:

Normal PCRB hybrid Flex time is available. Employee must be flexible when needed as projects or deadlines may sometimes necessitate extended hours.