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Afternoon Data Analyst R Programming Jobs in Arlington Heights, IL

Samprasoft

Data Analyst

Great Lakes, IL · On-site

Data Analyst As a Data Analyst in our client's Genomics Research Center's Bioinformatics ... Strong programming skills in Python for scripting and automation. Additional experience with R is ...

Samprasoft

Data Analyst - Inter

Chicago, IL · On-site

Re-engineer data processes and migrate the processes from on-premises to Amazon Web Services ... Experience with Python, SQL, Unix/Linux, Databricks, Tableau, R Shiny and Github * Experience with ...

City of New York

Data Analyst

Chicago, IL · On-site

Data Engineering & Automation: * Design, build, and maintain automated ETL pipelines (using tools ... Proficiency in a scripting language like Python or R for data analysis and statistical modeling (e ...

Tekcel8

Data Analyst

Chicago, IL

Basic understanding of Python or R for data analysis * Strong analytical and problem-solving skills * Good communication and presentation skills

Artech

Data Analyst - I

Chicago, IL · Hybrid

$30 - $35/hr

Collaborate with data engineers to enhance ETL workflows, metadata management, and data quality ... Strong experience with SQL and data querying tools (e.g., Snowflake, Toad, SAS, Python, R, Hive)

Capital One

Principal Data Analyst

Chicago, IL

Principal Data Analyst At Capital One, data is at the center of everything we do. When we launched ... Engineering, Mathematics discipline * Scripting experience in (Python, R, Spark, and SQL) * Strong ...

1872 Consulting

Data Analyst/BI Developer

Chicago, IL · On-site

... programming. We develop insights through alternative datasets and analytical methods to help fill ... Experience with R, PyData stack or other advanced analytics tools * Experience with Snowflake or ...

Next Step Systems

Quantitative Analyst

Northbrook, IL · On-site

Quantitative Analyst, Northbrook, IL - The Quantitative Analyst will assist in the research, design ... high-level programming language (R or Python). - Experience working with large data sets ...

TransUnion

Senior Data Analyst

Chicago, IL · On-site

$88.70K - $111.90K/yr

Foundational programming skills; experience in leveraging statistical language such as R or Python ... You will support the writing of programs for data extraction, segmentation and statistical analysis ...

Transunion

Senior Data Analyst

Chicago, IL

$67.50K - $112.50K/yr

Foundational programming skills; experience in leveraging statistical language such as R or Python ... You will support the writing of programs for data extraction, segmentation and statistical analysis ...

TransUnion

Senior Data Analyst

Chicago, IL · On-site

$88.60K - $111.80K/yr

Foundational programming skills; experience in leveraging statistical language such as R or Python ... You will support the writing of programs for data extraction, segmentation and statistical analysis ...

Trans Union LLC

Senior Data Analyst

Chicago, IL

$88.70K - $111.90K/yr

Foundational programming skills; experience in leveraging statistical language such as R or Python ... You will support the writing of programs for data extraction, segmentation and statistical analysis ...

DLA Piper

Sr Data Analyst

Chicago, IL · Hybrid

$88.70K - $111.90K/yr

The Senior Data Analyst, working in collaboration with and in support of the firm's strategic ... Highly proficiency in SQL and programming languages (Python/R/VBA) or other relevant programming ...

TransUnion

Senior Data Analyst

Chicago, IL

$88.60K - $111.80K/yr

Foundational programming skills; experience in leveraging statistical language such as R or Python ... You will support the writing of programs for data extraction, segmentation and statistical analysis ...

Dlapiper

Sr Data Analyst

Chicago, IL · Hybrid

$89.99K - $143.09K/yr

Summary The Senior Data Analyst, working in collaboration with and in support of the firm ... Highly proficiency in SQL and programming languages (Python/R/VBA) or other relevant programming ...

Apex Informatics

Data Analyst

Chicago, IL · On-site

Cannot work with OPT or CPT Description NTRS Asset and Market Data team is looking for an experienced and versatile Data Analytics Engineer to help us build a Security Master System. In this role ...

Honeycomb Insurance

Data Analyst

Chicago, IL

$120K - $170K/yr

This role bridges Finance, Accounting, and Engineering, ensuring that the data powering our ... Analytics Support for FP&A and Accounting * Create data assets enabling self-service dashboards and ...

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Afternoon Data Analyst R Programming information

See Arlington Heights, IL salary details

$34K

$82.6K

$136K

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

As of May 28, 2026, the average yearly pay for afternoon data analyst r programming in Arlington Heights, IL is $82,648.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

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 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 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.

Is data science dead in 10 years?

Data science, including roles like an Afternoon Data Analyst using R programming, is expected to remain relevant as organizations continue to rely on data-driven decision making. Advances in automation and AI may change specific tasks, but skills in data analysis, statistical methods, and programming will continue to be valuable in the foreseeable future.

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 Arlington Heights, IL? The most popular types of Data Analyst R Programming jobs in Arlington Heights, IL are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Arlington Heights, IL? For Afternoon Data Analyst R Programming jobs in Arlington Heights, IL, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Arlington Heights, IL look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Arlington Heights, IL are:
What cities near Arlington Heights, IL are hiring for Afternoon Data Analyst R Programming jobs? Cities near Arlington Heights, IL 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 Arlington Heights, IL as of May 2026, with employment types broken down into 78% Full Time, 14% Part Time, 5% Contract, and 3% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $82,648 per year, or $39.7 per hour.
Data Analyst

Data Analyst

Samprasoft

Great Lakes, IL • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Data Analyst

As a Data Analyst in our client’s Genomics Research Center’s Bioinformatics Engineering team, you will be responsible for developing and running workflows to standardize and load project datasets in a centralized environment. You will work closely with Bioinformatics Engineering, as well as therapeutic area facing bioinformatics research scientists to leverage common data models, and support GRC Bioinformaticians’ needs for loading and querying. Your expertise in PostgreSQL for database management and Python and R for scripting and automation will be crucial in developing and maintaining ETL processes to ensure data quality and integrity.

Responsibilities
  • Develop and maintain a functional understanding of the GRC common data models, loading processes, and requirements, and perform accurate and efficient loading of new and historical datasets into the GRC’s Omics Data Server.
  • Collaborate with Bioinformatics Engineers to develop and implement additional data loading workflows.
  • Partner with Bioinformatics research scientists to identify, process, and load project data into the common data models.
  • Build and execute ETL processes to integrate non-GRC generated high-value datasets into the common data models.
  • Keep thorough documentation for tracking datasets and loading tasks.
  • Ensure reproducibility and facilitate collaboration with team members by documenting and versioning code with git.
Qualifications
  • Bachelor's degree in computer science, bioinformatics, or a related field +3 years of experience.
  • Experience with building and running workflows for RDMS data loading and ETL processes.
  • Proficient in PostgreSQL (or equivalent) and ability to write complex queries for data extraction and analysis.
  • Strong programming skills in Python for scripting and automation. Additional experience with R is preferred.
  • Familiarity with genomic data formats and databases commonly used in bioinformatics research.
  • Knowledge of data modeling concepts and implementing common data models in a relational database.
  • Familiarity with data cleaning, normalization, and quality control processes.
  • Excellent communication skills and ability to collaborate with researchers and stakeholders.

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