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Afternoon Data Analyst R Programming Jobs in Orlando, FL

Data Analyst

Orlando, FL ยท On-site

$70 - $100/hr

Certifications in data analysis software (such as SAS, R, Python), big data technologies, or business intelligence platforms like Tableau or Power BI are highly desirable. 2. Professional Experience:

New

We are seeking a detail-oriented and analytical Data Analyst to join our team in Orlando. You will ... Programming & Querying: Develop complex SQL queries and utilize ETL frameworks to extract ...

Data Analyst

Orlando, FL ยท On-site

$120K/yr

We are seeking a detail-oriented and analytical Data Analyst to join our team in Orlando. You will ... Programming & Querying: Develop complex SQL queries and utilize ETL frameworks to extract ...

Sr. Data Analyst

Orlando, FL

$80K - $101K/yr

... feature engineering techniques, and scalable transformation processes to ensure accuracy ... Advanced skills in SQL, Python and/or R * Familiarity in visualization tools such as Tableau ...

Sr. Data Analyst

Orlando, FL

$80K - $101K/yr

... feature engineering techniques, and scalable transformation processes to ensure accuracy ... Advanced skills in SQL, Python and/or R * Familiarity in visualization tools such as Tableau ...

The analyst will work closely with the Data Product Owner, Data Engineering Lead, and various business teams to improve how data is accessed, maintained, and leveraged. This position plays a critical ...

The analyst will work closely with the Data Product Owner, Data Engineering Lead, and various business teams to improve how data is accessed, maintained, and leveraged. This position plays a critical ...

Data Analyst

Orlando, FL ยท On-site

$70 - $110/hr

Partner with engineering and product teams to resolve data issues and enforce standards ... Qualifications * 3-5 years of experience in data analysis, data governance, or data stewardship.

Senior Data Analyst - CRM

Orlando, FL ยท On-site

$80 - $100/hr

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, or a related ... Experience with data analysis and visualization tools such as Python, R, SQL, Power BI, Tableau, or ...

Senior Data Analyst

Altamonte Springs, FL ยท On-site

$80K - $101K/yr

... Analyst (not an engineering role) with strong SQL expertise and experience in Snowflake data warehousing, ETL pipeline development, and enterprise reporting. This position requires AI and Cortex ...

Role: Senior Data Analyst/ Business Analyst Location: Orlando - Florida (Onsite) Duration: 12 ... engineering BI and product teams for end-to-end delivery Strong stakeholder communication and ...

As a Data Analyst you will * Assess existing workflows, challenge legacy processes, and help design ... Lead process re-engineering initiatives across Middle Office to simplify workflows, eliminate ...

Lead process re-engineering initiatives across Middle Office to simplify workflows, eliminate ... Apply data analysis and process metrics to evaluate performance, identify bottlenecks, and measure ...

FIU Fraud Data Analyst

Sanford, FL ยท On-site

$75 - $120/hr

Familiarity with Python, R, SAS, model monitoring, statistical analysis, or machine learning ... engineering, mule activity, mobile, digital, check, ACH, wire, debit card, and payment fraud;

New

Data Science Tutor

Orlando, FL 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 ...

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Afternoon Data Analyst R Programming information

See Orlando, FL salary details

$31.7K

$77.1K

$127K

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

As of Aug 20, 2026, the average yearly pay for afternoon data analyst r programming in Orlando, FL is $77,146.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,300.00 and $90,600.00 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 are the most commonly searched types of Data Analyst R Programming jobs in Orlando, FL?

The most popular types of Data Analyst R Programming jobs in Orlando, FL are:

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

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

What cities near Orlando, FL are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Orlando, FL with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in Orlando, FL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $77,146 per year, or $37.1 per hour.

$70 - $100/hr

Other

Posted 2 days ago

New


Job description

  • Minimum Requirement: Bachelor's degree in Data Science, Statistics, Computer Science, Information Management, or a related field.
  • Preferred Qualification: Master's degree in Data Science, Business Analytics, or a related discipline.
  • Certifications: Certifications in data analysis software (such as SAS, R, Python), big data technologies, or business intelligence platforms like Tableau or Power BI are highly desirable.
2. Professional Experience:
  • Minimum Years of Experience: At least 3-5 years of experience in data analysis, preferably within the sectors relevant to the project such as government, healthcare, or public administration.
  • Specific Experience: Experience with managing and analyzing large datasets, creating reports, and providing actionable insights. Experience in working with compliance or regulatory data within a structured project environment is a plus.
3. Skills and Competencies:
  • Analytical Skills: Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Technical Skills: Proficiency in database management and data analysis software (e.g., SQL, Python, R), as well as advanced proficiency in spreadsheet tools like Microsoft Excel.
  • Communication Skills: Excellent communication skills to effectively present findings and insights to both technical and non-technical stakeholders.
4. Knowledge:
  • Statistical and Mathematical Knowledge: Solid understanding of statistical testing and modeling techniques that are essential for analyzing complex data.
  • Data Privacy and Security Knowledge: Awareness of data privacy standards and best practices, especially in handling sensitive or personal data, which is crucial in government and healthcare sectors.
  • Problem-solving Abilities: Ability to approach complex data-related problems with a clear analytical methodology and solve them efficiently.
  • Attention to Detail: Meticulous attention to detail to ensure the accuracy of data and analysis.
  • Proactivity: Proactive in identifying trends, anomalies, and opportunities in the data to drive project objectives.
6. Responsibilities:
  • Data Collection and Management: Collect, process, and clean data from multiple sources to ensure it is ready for analysis.
  • Data Analysis and Reporting: Analyze data using statistical techniques and tools, and create reports and dashboards that clearly communicate the findings and recommendations.
  • Support Decision Making: Provide data-driven insights to support strategic decisions and project initiatives.
  • Continuous Learning: Stay updated with the latest trends, tools, and technologies in data analysis to enhance project outcomes and efficiency.

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