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Entry Level Data Analyst R Programming Jobs in Pittsburgh, PA

Data Analyst Location: Pittsburgh, PA Onsite position Fulltime Position *****NO C2C**** JD * Data ... Programming Languages: Familiarity with languages like Python or R. * Data Cleaning and Preparation:

... , Data, and Software Engineering, servicing an array of noteworthy financial services and ... Conduct data analysis to identify patterns, correlations, and insights. * Collaborate with cross ...

Analyst

Pittsburgh, PA · On-site

$100K - $110K/yr

Experience with data visualization tools (Power BI, Tableau). * Basic programming knowledge (Python or R). * Strong analytical and problem-solving abilities. * Good communication and presentation ...

The ideal candidate is experienced and comfortable with analyzing big data and crunching numbers, is familiar with the electricity wholesale markets in the US, and has programming background ...

The ideal candidate is experienced and comfortable with analyzing big data and crunching numbers, is familiar with the electricity wholesale markets in the US, and has programming background ...

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 ...

As a Data Protection Senior Analyst, you'll support the delivery of data protection, data ... Prior internship, academic project, or entry-level experience in security or compliance is a plus.

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Entry Level Data Analyst R Programming information

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$12

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$59

How much do entry level data analyst r programming jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for entry level data analyst r programming in Pittsburgh, PA is $31.97, according to ZipRecruiter salary data. Most workers in this role earn between $20.53 and $35.72 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Analyst R Programming vs Data Scientist?

AspectEntry Level Data Analyst R ProgrammingData Scientist
Required SkillsBasic R programming, data cleaning, visualization, ExcelAdvanced R, Python, machine learning, statistical modeling
Work EnvironmentBusiness, finance, marketing teamsResearch, tech, healthcare, diverse industries
CertificationsData analysis, R programming coursesData science, machine learning certifications

Entry Level Data Analyst R Programming roles focus on data cleaning, visualization, and basic analysis using R, often within business environments. Data Scientists require advanced statistical and programming skills, including machine learning, and work on complex predictive models across various industries. While both roles involve data handling, Data Scientists typically have a broader skill set and handle more complex projects.

What is an Entry Level Data Analyst (R Programming)?

An Entry Level Data Analyst (R Programming) is a professional who uses the R programming language to collect, process, and analyze data to help organizations make informed decisions. They typically work with large datasets, create visualizations, and generate reports under the guidance of more experienced analysts. Entry-level data analysts are often responsible for basic data cleaning, statistical analysis, and supporting team projects while they develop their skills in R and data analysis techniques.

What are the key skills and qualifications needed to thrive as an Entry Level Data Analyst specializing in R Programming, and why are they important?

To thrive as an Entry Level Data Analyst specializing in R Programming, you need a solid grounding in statistics, data cleaning, and analytical methods, typically supported by a relevant degree such as statistics, mathematics, or computer science. Proficiency in R programming, familiarity with data visualization tools (e.g., ggplot2), and experience with spreadsheet software or SQL are commonly required. Strong attention to detail, problem-solving abilities, and clear communication skills set outstanding candidates apart in this role. These skills are crucial to accurately interpret data, deliver actionable insights, and effectively collaborate with teams to support data-driven decision-making.

What are some typical challenges entry-level data analysts face when working with R programming in a team setting?

Entry-level data analysts using R often encounter challenges such as adapting to existing codebases, understanding team-specific data workflows, and ensuring code reproducibility and documentation for collaborative projects. New analysts may also need to quickly learn version control practices (like using Git) and follow standardized procedures for data cleaning and reporting. Regular communication with senior analysts and participation in code reviews are essential to build both technical proficiency and teamwork skills.
What are the most commonly searched types of Data Analyst R Programming jobs in Pittsburgh, PA? The most popular types of Data Analyst R Programming jobs in Pittsburgh, PA are:
What are popular job titles related to Entry Level Data Analyst R Programming jobs in Pittsburgh, PA? For Entry Level Data Analyst R Programming jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Analyst R Programming jobs in Pittsburgh, PA look for? The top searched job categories for Entry Level Data Analyst R Programming jobs in Pittsburgh, PA are:
What cities near Pittsburgh, PA are hiring for Entry Level Data Analyst R Programming jobs? Cities near Pittsburgh, PA with the most Entry Level Data Analyst R Programming job openings:
Infographic showing various Entry Level Data Analyst R Programming job openings in Pittsburgh, PA as of June 2026, with employment types broken down into 2% As Needed, 25% Full Time, 64% Part Time, and 9% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $66,489 per year, or $32 per hour.

Data Analyst

Sarian, Inc.

Pittsburgh, PA • On-site

Full-time

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


Job description

Role: Data Analyst
Location: Pittsburgh, PA
Onsite position
Fulltime Position
*****NO C2C****
JD
  • Data Conditioning - identification of appropriate test data, conditioning of test data as necessary to meet non-functional testing requirements.
  • Statistical Analysis: Proficiency in statistical methods and techniques.
  • SQL: Knowledge of Structured Query Language for database management.
  • Data Visualization Tools: Experience with tools like Tableau, Power BI.
  • Programming Languages: Familiarity with languages like Python or R.
  • Data Cleaning and Preparation: Skills in data cleaning, transformation, and quality assurance.
  • Data Modeling: Ability to design and implement data models.
  • Communication and Presentation: Strong communication and presentation skills to effectively convey findings to stakeholders.
  • Critical Thinking: Ability to analyze data, identify trends, and draw conclusions.
  • Attention to Detail: Accuracy and precision in data analysis and reporting.
  • Data Conditioning - identification of appropriate test data, conditioning of test data as necessary to meet non-functional testing requirements.
  • Data Collection and Preparation: Gathering data from various sources, cleaning and preparing it for analysis, and ensuring data quality.
  • Statistical Analysis: Performing statistical analyses to identify trends, patterns, and anomalies in the data.
  • Exploratory Data Analysis (EDA): Engaging in exploratory data analysis to gain a deeper understanding of the data and identify potential areas for further investigation.
  • Data Visualization: Creating clear and concise visualizations (charts, graphs, dashboards) to communicate data insights effectively.
  • Reporting and Presentation: Preparing reports and presentations to communicate findings to stakeholders, influencing decision-making.
  • Data Governance and Quality: Ensuring data quality, process documentation, and defining Key Performance Indicators (KPIs).
  • Database Management: Managing databases, troubleshooting data-related issues, and optimizing database performance.
  • Data Modeling: Building data models to represent and analyze data effectively.
  • Data Mining: Mining data from various sources and transforming it into usable formats.

Manikanth
Sarian Solutions, Inc.
Ph: 732-790-2266 X 105
manikanth.d@sariansolutions.com | https://www.sarianinc.com/