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Afternoon Data Analyst R Programming Jobs in Liberty, MO

Pwc

Data Governance- Manager

Kansas City, MO

$99K - $232K/yr

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

Seaboard

Data and Analytics Manager

Merriam, KS · On-site

... the afternoon, and coach a junior analyst at the end of the day. At this team size, the manager ... Work with the Data Engineer to establish and monitor data quality frameworks * Ensure compliance ...

Sporting Kansas City

Data Scientist

Kansas City, KS · On-site

Develop strong relationships with the wider Data and Analytics team, ensuring alignment with Club and department strategy. * Work very closely with the First Team Data Engineer to ensure advanced ...

AEG

Data Scientist

Kansas City, KS · On-site

Develop strong relationships with the wider Data and Analytics team, ensuring alignment with Club and department strategy. * Work very closely with the First Team Data Engineer to ensure advanced ...

Clarivate

Data Security Analyst

Kansas City, KS · Hybrid

We are looking for a Data Security Analyst to join our Information Security Architecture team in ... Provide configuration-level guidance to engineering and business teams on secure handling of ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Liberty, MO

Afternoon Data Analyst R Programming information

See Liberty, MO salary details

$32.1K

$78K

$128.3K

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

As of Sep 3, 2026, the average yearly pay for afternoon data analyst r programming in Liberty, MO is $77,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $91,500.00 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 Liberty, MO look for?

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

What cities near Liberty, MO are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Liberty, MO with the most Afternoon Data Analyst R Programming job openings:

Afternoon Data Analyst R Programming jobs near you

Senior Specialist, Data Science

Kansas City International

Kansas City, MO • On-site

$121 - $140/hr

Other

Posted 16 days ago

Key responsibilities

  • Develop and implement advanced statistical and machine learning models to analyze operational datasets and generate predictive insights.

  • Design and build scalable data pipelines and feature engineering processes to support model development, training, and deployment.

  • Create data visualizations and analytical reports to communicate model outputs, trends, and key performance indicators.

Job description

Senior Specialist, Data Science (Soo Line Railroad Company, Kansas City, Missouri)
  • Develop and implement advanced statistical and machine learning models to analyze large-scale operational datasets and generate predictive insights related to performance, reliability, and efficiency;
  • Design and build scalable data pipelines and feature engineering processes to support model development, training, and deployment;
  • Perform exploratory data analysis and apply statistical techniques to identify patterns, trends, and relationships across complex datasets;
  • Develop predictive models for use cases such as demand forecasting, anomaly detection, predictive maintenance, and operational optimization;
  • Evaluate model performance using appropriate metrics and refine models to improve accuracy, robustness, and generalizability;
  • Integrate machine learning models into production environments, collaborating with engineering teams to support deployment and monitoring;
  • Analyze large and complex datasets using programming languages such as Python and SQL, and leverage libraries for statistical analysis and machine learning;
  • Design experiments and conduct hypothesis testing to support data-driven decision-making and validate business assumptions;
  • Translate business problems into analytical frameworks and communicate findings, insights, and recommendations to technical and non-technical stakeholders;
  • Develop and maintain documentation for data models, methodologies, and analytical processes to support reproducibility and governance;
  • Collaborate with cross-functional teams to identify opportunities for applying advanced analytics and to align modeling approaches with business objectives;
  • and Create data visualizations and analytical reports to communicate model outputs, trends, and key performance indicators.

Salary: $120,723 - 140,000 per year.

MINIMUM REQUIREMENTS: Bachelor's degree or its U.S. equivalent in Computer Science, Information Systems, Information Technology, Computer Engineering, or a related field, plus 5 years of professional experience as a Software Engineer, Data Analyst, or any occupation, job title, position involving conducting data analysis, data manipulation, automation and statistical analysis.

In lieu of a Bachelor's degree plus 5 years of experience, the employer will accept a Master's degree or its U.S. equivalent in Computer Science, Information Systems, Information Technology, Computer Engineering, or a related field, plus 3 years of professional experience as a Software Engineer, Data Analyst, or any occupation, job title, position involving conducting data analysis, data manipulation, automation and statistical analysis.

Must also have experience in the following:
  • 3 years of professional experience conducting data analysis using SQL, including data profiling, data validation, and extracting actionable insights from large data sets;
  • 3 years of professional experience writing, optimizing, and troubleshooting advanced SQL queries, including complex joins, aggregations, subqueries, stored procedures, functions, and performance tuning in relational databases;
  • 3 years of professional experience performing data manipulation, automation, and statistical analysis, including building and maintaining data pipelines and ETL processes to integrate data from multiple automotive-related data sources;
  • 3 years of professional experience applying statistical analysis and predictive modeling techniques, including regression analysis, time-series forecasting, and machine learning, to operations data for insights including predictive maintenance and capacity forecasting;
  • 3 years of professional experience documenting SQL queries, logic, data workflows, and analytics results for technical and non-technical stakeholders;
  • and 3 years of professional experience collaborating with cross-functional teams, including business, IT, and finance, to gather requirements, clarify business needs, and deliver solutions strictly using SQL.
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