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Afternoon Data Analyst R Programming Jobs in Parkville, MO

Garmin Ltd.

Data Scientist 2

Olathe, KS · On-site

$110 - $160/hr

... analysis, and data engineering techniques to address challenging business problems. Essential ... Experience using systems such as SQL, Python, or R * Strong knowledge of machine learning ...

Pwc

Data Governance- Manager

Kansas City, MO · On-site

$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 ...

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

Afternoon Data Analyst R Programming information

See Parkville, MO salary details

$32.9K

$80K

$131.7K

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

As of Sep 4, 2026, the average yearly pay for afternoon data analyst r programming in Parkville, MO is $80,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,500.00 and $93,900.00 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 cities near Parkville, MO are hiring for Afternoon Data Analyst R Programming jobs?

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

Afternoon Data Analyst R Programming jobs near you

Data Scientist

Sunixa Solutions Inc

Overland Park, KS • On-site

$50 - $55/hr

Full-time

Posted 2 days ago

New

Job description

# Only on W2
DATA SCIENTIST
Location: Overland park, Kansas
Exp: 6-7+
Duration: Long term

Job Summary:
We are looking for a skilled Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. You will be responsible for building predictive models, developing machine learning algorithms, and delivering data-driven insights to stakeholders

Key Responsibilities:
Collect, clean, and process large datasets from various sources
Build, train, and deploy machine learning models and statistical models
Perform exploratory data analysis (EDA) and feature engineering
Develop predictive analytics and forecasting solutions
Work with engineering team to deploy models into production
Create data visualizations and reports for business stakeholders
Collaborate with product, marketing, and business teams to understand requirements.

Required Skills:
Strong programming skills in Python / R, SQLHands-on experience with Machine Learning, Deep Learning, NLPExperience with libraries like Pandas, NumPy, Scikit-learn, TensorFlow, PyTorchExperience with Data Visualization tools - Tableau, Power BI, MatplotlibKnowledge of Big Data technologies - Spark, Hadoop (plus point)Experience with Cloud platforms - AWS / Azure / GCPStrong analytical and problem-solving skills