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Afternoon Data Analyst R Programming Jobs in Louisiana

Pwc

Data Governance- Manager

New Orleans, LA

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

IBM

AI, Analytics, Automation & Data Services - focused on helping organizations modernize data ... Basic understanding of programming concepts with exposure to Python, SQL, Java, or similar ...

Pwc

Data Strategy & Governance -Director

New Orleans, LA

$155K - $410K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Meta

Data Center Capacity Engineer

Rayville, LA

$111K/yr

Proficiency in programming and scripting languages such as SQL, R, Python, Bash, or other ... process analysis methodologies, visualization, and modeling * Project management and delivery ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Louisiana

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 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 Louisiana?

The most popular types of Data Analyst R Programming jobs in Louisiana are:

What are popular job titles related to Afternoon Data Analyst R Programming jobs in Louisiana?

For Afternoon Data Analyst R Programming jobs in Louisiana, the most frequently searched job titles are:

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

The top searched job categories for Afternoon Data Analyst R Programming jobs in Louisiana are:

What cities in Louisiana are hiring for Afternoon Data Analyst R Programming jobs?

Cities in Louisiana 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 Louisiana as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Clinical Data Scientist

RedSail Technologies, LLC

Shreveport, LA • On-site, Remote

$140K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago

Job description

Clinical Data ScientistJob Summary

The RedSail Advantage Solutions has the primary mission to create incremental value streams for RedSail through the development and activation of Clinical, Financial, & Operational Programs that leverage our uniquely integrated technology platforms as well as our associated reach within the targeted market segments. The Clinical Data Scientist, will participate in the making use of RedSail’s data to evaluate and establish various impactful programs to accomplish and assist with the measurement of program effectiveness against the department objectives.

Key Duties
  • Data Collection: Gathering data from various sources, such as databases, APIs, web scraping, and more. This can involve collecting structured and unstructured data.
  • Data Cleaning: Preprocessing the collected data to handle missing values, remove duplicates, correct inconsistencies, and address outliers. This step ensures data quality and reliability.
  • Data Exploration (Exploratory Data Analysis, EDA): Analyzing the main characteristics of the data often through visualization and summary statistics. This helps in understanding data distributions, relationships between variables, and identifying patterns or anomalies.
  • Data Transformation: Modifying data into a suitable format for analysis, such as normalization, standardization, or creating new features (feature engineering).
  • Data Visualization: Creating visual representations of data, such as graphs, charts, and dashboards, to communicate findings effectively. Tools like Matplotlib, Seaborn, and Tableau are commonly used.
  • Statistical Analysis: Applying statistical methods to understand data distributions, test hypotheses, and infer relationships. This can include t-tests, chi-square tests, ANOVA, and regression analysis.
  • Data Communication: Presenting findings, insights, and recommendations to stakeholders through reports, presentations, and storytelling. Effective communication is crucial for decision-making.
  • Collaboration with Domain Experts: Working with professionals from various fields to ensure that the data science approach aligns with business goals and that the results are meaningful and actionable.
  • Keeping Up with Industry Trends: Continuously learning and adapting to new tools, technologies, and methodologies in data science to stay current and effective in the field.
  • Ethical Considerations and Compliance: Ensuring that data usage complies with ethical standards and legal regulations, such as data privacy laws (e.g., HIPAA)
Education/Training
  • Bachelor’s degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree. Doctor of Pharmacy with data credentials or extensive data experience may substitute for formal education in Data Science.
Required Work Skills/Experience
  • Pharma/Pharmacy/Healthcare experience.
  • Experience programming with SQL scripting.
  • Experience with data analytics visualization tools such as PowerBI and Tableau.
  • Ability to transform complex data across multiple platforms into concise datasets.
  • Ability to visualize data in the most effective way possible for a given project or study.
  • Strong analytical and problem-solving skills; inquisitive.
  • Ability to work independently and with team members from different backgrounds and collaborative styles.
  • Excellent attention to detail with critical thinking skills.
Preferred Work Skills/Experience
  • A combination of both Doctor of Pharmacy and degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree (i.e. Pharmacist Data Scientist) strongly preferred.
  • 2 years of experience as a Data Analyst, Data Scientist or Data Engineer.
  • Experience with Pharma/Pharmacy transactions.
  • Experience programming with Python or Go Lang.
Discretionary Judgement
  • Uses independent judgment and discretion based upon the employee’s experience in the position and knowledge of the products, equipment, and services.
  • Uses good judgment and possesses ethical work values.
Physical Demands/Working Conditions/General Employment
  • Moderate or high stress levels may be experienced in the job performance.
  • Position is performed in a general office environment, home office, or approved remote workspace where physical work includes, but is not limited to, sitting, standing, reaching, kneeling, bending, and lifting to 25 lbs.
Equipment
  • Daily use of Microsoft Teams (phone), computer, printer, and other routine office equipment.
  • Must have reliable and consistent internet access.
Safety to Self and Others
  • Little responsibility for the safety of others. Job is performed in an office setting where there are no hazardous materials or equipment.
Working Conditions/Hazards
  • Position is performed in an open office environment or approved remote work location.
Compensation & Total Rewards
  • The anticipated base salary range for this position is $140,000-$145,000 annually. This position is also eligible for an annual target bonus of 4%. Actual compensation will be determined based on factors including relevant experience, skills, qualifications, and geographic location.
  • Benefits include paid time off, medical, dental, and vision insurance, a 401(k) with a 5% company match, a fitness bonus, professional development opportunities, and programs that support overall well-being.
Work Location
  • Hybrid at a RedSail Office
    • Spartanburg, SC
    • Irving, TX
    • Shreveport, LA
    • Oak Brook, IL
    • Cranberry Township, PA
    • Long Island, NY

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