1

Afternoon Data Analyst R Programming Jobs in Texas

Data Analysis & Solution Development * Analyze Loopbacks large-scale healthcare data warehouse ... Exposure to SQL and at least one scripting/statistical language (Python, R). * Exceptional problem ...

Data Analyst

Dallas, TX ยท On-site +1

The Data Analyst (SQL) will be primarily responsible for the following: * Integrate data from ... R, or other). * Must be detail-oriented with excellent analytical and quantitative skills.

... Data Analyst will support operational and strategic decision-making by implementing data pipelines ... of programming languages such as Python, R, Matlab or similar is highly preferred โ€ข Advanced ...

Data Analyst

Dallas, TX ยท On-site

Data Analyst Category: Software Development/ Engineering Main location: United States, Texas, Dallas Alternate Location(s): United States, Pennsylvania, Pittsburgh Position ID:J0626-0213 Employment ...

We are in search of an experienced data & analytics mind to help drive Pizza Hut's digital ... Strong experience with programming language such as SQL, Python, R, etc. to perform statistical ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

Digital Data Analyst

Plano, TX ยท On-site

$99K - $115K/yr

We are in search of an experienced data & analytics mind to help drive Pizza Hut's digital ... Strong experience with programming language such as SQL, Python, R, etc. to perform statistical ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

Collaborate with business users, data architects, developers, and project teams to gather and document requirements. . Conduct root cause analysis and data quality investigations to resolve data ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

This role collaborates with data engineers to visualize data from all kinds of sources within the manufacturing factory setting. The data analyst will analyze, design, create, maintain, update ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives. Design, build, and maintain ...

next page

Showing results 1-20

Afternoon Data Analyst R Programming information

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 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.

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 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 the most commonly searched types of Data Analyst R Programming jobs in Texas? The most popular types of Data Analyst R Programming jobs in Texas are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Texas look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Texas are:
What cities in Texas are hiring for Afternoon Data Analyst R Programming jobs? Cities in Texas with the most Afternoon Data Analyst R Programming job openings:
RWD Data Analyst

RWD Data Analyst

Loopback Analytics

Dallas, TX โ€ข On-site

Full-time

Posted 3 days ago


Job description

Salary: $25-$35 / hour

This employer will not sponsor applicants for employment visa status (e.g., H1-B) for this position. All applicants must be currently authorized to work in the United States on a full-time basis.

Role Summary

Loopback Health is hiring an innovative and team-oriented RWD Data Analyst who will work closely with Loopback Real World Data and Data Operations teams. This position will give exposure to how healthcare data is used to support clinical research across various Life Sciences stakeholders, including pharmaceuticals, medical device, and regulatory functions.


Key Responsibilities:

Data Analysis & Solution Development

  • Analyze Loopbacks large-scale healthcare data warehouse (claims, EHR, pharmacy, etc.) to support answering clinical research feasibility questions across various therapy areas.
  • Assist in developing reporting tools that help non-technical stakeholders understand the data asset.
  • Synthesize and communicate analytical findings to team members.

Cross-Functional Collaboration & Continuous Improvement

  • Collaborate with Sales, Client Success, Product, and Operations teams to improve data quality, documentation, and product features.
  • Gather and document customer feedback to inform future data product development.



Qualifications

Required:

  • Bachelors degree (completed or working towards) in a quantitative or life sciences field (e.g., Statistics, Bioinformatics, Epidemiology, Computer Science, Pharmacy, Public Health, or related).
  • Exposure to SQL and at least one scripting/statistical language (Python, R).
  • Exceptional problem-solving skills with the ability to break down ambiguous client questions into actionable analyses.
  • Strong communication skills, both verbal and written, with an ability to explain complex data concepts to non-technical audiences.
  • Comfortable working in a fast-paced, cross-functional team environment.

Soft Skills

  • Data-driven and analytically rigorous, with a focus on delivering client value.
  • Creative, resourceful, and comfortable with ambiguity.
  • Strong collaborator who thrives in a team-oriented, rapidly evolving environment.
  • Interest in using AI-assisted tools for data analysis, coding, or workflow efficiency


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or national origin.