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Afternoon Data Analyst R Programming Jobs in Shelton, WA

Environmental Data Analyst

Olympia, WA ยท On-site

$76 - $110/hr

Work with multi-disciplinary teams of engineers and scientists to support statistical and spatial ... Experience using Python and/or R (Tidyverse, Shiny) for data analysis, visualization, dashboards ...

The Data Analytics Team Lead will be responsible for the oversight of the Data Analytics team and ... Assists platform engineers, account personnel, and external clients with daily workflow ...

Manager, Data Engineer (Remote)

Home, WA ยท Remote

$100K - $174K/yr

Job Summary Strategic Analytics at Arch is a growing team at the forefront of the company's AI ... Own end-to-end data engineering delivery across the project lifecycle. * Build strong partnerships ...

Manager, Data Engineer (Remote)

Home, WA ยท Remote

$100K - $174K/yr

Job Summary Strategic Analytics at Arch is a growing team at the forefront of the company's AI ... Own end-to-end data engineering delivery across the project lifecycle. * Build strong partnerships ...

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... September 27, 2026 Engineering postings close: October 2, 2026 Interviews: Early to mid October ...

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... September 27, 2026 Engineering postings close: October 2, 2026 Interviews: Early to mid October ...

Programming Engineer (TE4)

Olympia, WA ยท On-site +1

$88K - $119K/yr

... Programming Engineer in Spokane, WA. In this role, you will develop projects that improve and ... Ability to identify system deficiencies through data analysis and field insights, determine ...

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Afternoon Data Analyst R Programming information

See Shelton, WA salary details

$35.1K

$85.4K

$140.6K

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

As of Sep 4, 2026, the average yearly pay for afternoon data analyst r programming in Shelton, WA is $85,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,600.00 and $100,300.00 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 Shelton, WA look for?

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

What cities near Shelton, WA are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Shelton, WA with the most Afternoon Data Analyst R Programming job openings:

Environmental Data Analyst

GSI Environmental Inc.

Olympia, WA โ€ข On-site, Remote

$76K - $110K/yr

Full-time

Re-posted 28 days ago


Job description

Description

GSI is seeking an Environmental Data Analyst who combines technical ability, analytical creativity, and business acumen to strengthen our data management, analysis, and visualization team. The ideal candidate is comfortable across the full data lifecycleโ€”building and maintaining relational databases, developing analysis and automation pipelines in SQL, Python, and/or R, and providing query, reporting, and visualization support in a collaborative organization working closely with technical staff. Familiarity with environmental chemistry data generated from field investigations of water, soil, sediment, air, and biological matrices is valued. The candidate should know how to analyze system requirements and be familiar with relational databases, statistical analysis, and modern data visualization techniques using relevant and current tools.

GSI provides high-quality technical and regulatory expertise to industry and government to address a broad range of environmental issues. We specialize in solving complex environmental problems by leveraging our extensive knowledge of environmental regulations, stressing accurate data collection and analysis, and applying new technologies to our clients' most difficult challenges.

Responsibilities

  • Support environmental investigation projects by maintaining relational databases of environmental chemistry data from historical reports, laboratory test results, web sources, and third-party databases.
  • Build and maintain ETL (extract, transform, load) and analysis workflows in SQL, Python, and/or R to clean, transform, validate, and analyze environmental datasets.
  • Work with multi-disciplinary teams of engineers and scientists to support statistical and spatial analyses.
  • Build dashboards and visualizations, and format tables, charts, and graphs to style guidelines for technical reports and presentations.
  • Organize data in structures that support automation and downstream analysis.
  • Perform quality assurance on analytical databases to ensure data integrity, and identify and correct data gaps, errors, and relational table issues.
  • Support a wide variety of projects ranging from litigation support and site investigation to data mining for research and development.
  • Effectively communicate findings to internal and external clients.
  • Complete assigned tasks on schedule and within budget while meeting quality standards on deliverables.
  • BS/BA or higher degree in data science, computer science, statistics, environmental science, or a related field.
  • 2-5 years of work experience in data management or analysis, with strong relational database skills using PostgreSQL, Microsoft SQL Server, Microsoft Access, or other database management systems.
  • Comfortable writing advanced SQL for data management (beyond basic create, read, update, delete), to clean, transform, and structure data in relational databases.
  • Familiarity with relational database design, data modeling, and normalization.
  • Awareness of data compilation, migration, and backup/retention considerations.
  • Shell scripting (Bash) and comfort working in Linux and command-line environments.
  • Experience using Python and/or R (Tidyverse, Shiny) for data analysis, visualization, dashboards, and web applications, including hands-on project work.
  • Self-motivated and eager to learn, with a drive to adopt new data and analysis techniques, AI, and emerging technologies to improve workflows.
  • Excellent written and verbal communication, and the ability to manage multiple tasks and meet deadlines with limited supervision.
  • Strong problem-solving skills and attention to detail.
  • Additional preferred skillsets and qualifications include:
    • Familiarity with chemistry data, laboratory information management systems (LIMS), data validation, and extraction of data from online sources.
    • Version control (Git) and reproducible, scripted analysis workflows.
    • Application development and deployment, including web frameworks for data tools (e.g., Django, Flask/FastAPI, Dash, Streamlit, R Shiny). Familiarity with containerization (Docker) is a plus.
    • Experience with embedded and analytical database engines (e.g., SQLite, DuckDB) for local analysis, prototyping, and data interchange.

Job Perks

  • Competitive salary and benefits
  • Quarterly and year-end bonuses
  • Flexible work environment with potential for remote work
  • On-the-job training, mentorship, and professional development
  • Participation in conferences, technical presentations, and papers
  • Collaborative atmosphere
  • Base salary will vary depending on qualifications and experience.

The anticipated salary range for this position is $76,000โ€“$110,000. This range represents GSI's good-faith estimate of the base salary for the position and is provided in accordance with applicable pay transparency laws. Starting salary will be determined based on several job-related factors, including relevant experience, education, professional licensure, certifications, technical expertise, geographic location, internal equity, and overall qualifications.