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Afternoon Data Analyst R Programming Jobs in Missouri

Boeing

Data Integration Analyst

Saint Louis, MO

The analyst will collaborate closely with data SMEs, software developers, data scientists, and the ... F.R. 120.15 is required. "U.S. Person" includes U.S. Citizen, lawful permanent resident, refugee ...

Varsity Tutors

Data Science Tutor

Columbia, MO · 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 ...

Varsity Tutors

Data Science Tutor

Kansas City, MO · 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 ...

Varsity Tutors

Data Science Tutor

Saint Louis, MO · 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 ...

Equifax, Inc.

Senior Data Analyst, Finance

Saint Louis, MO · On-site

$83K - $105K/yr

The Senior Data Analyst, Finance is responsible for identifying Finance user requirements and ... Architect ETL pipelines using SQL, Python, and JSON to engineer robust data sources that drive high ...

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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.

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 Missouri? The most popular types of Data Analyst R Programming jobs in Missouri are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Missouri? For Afternoon Data Analyst R Programming jobs in Missouri, the most frequently searched job titles are:
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What cities in Missouri are hiring for Afternoon Data Analyst R Programming jobs? Cities in Missouri with the most Afternoon Data Analyst R Programming job openings:
Afternoon Data Analyst R Programming jobs near you
Remote Data Analyst/ Dashboard Developer

Remote Data Analyst/ Dashboard Developer

TriOptus LLC

Saint Louis, MO • On-site, Remote

Other

Re-posted 6 days ago

Job description

Job Code - Data Analyst / Dashboard Developer
Duration - 3 year contract
Description: The Continuous Improvement team is seeking an energetic and experienced individual for a position in data analytics. This role is responsible for analyzing data, identifying, and resolving data discrepancies, across multiple business applications specializing in transforming reporting and analytics across key areas of the business. This role will be involved in improving, and arming our leaders with the right reports, tools, and insights to drive the business. It entails applying rigor to the existing reporting and analytics landscape and understanding how to realize benefits across visualization, automation, and consumption of information that ultimately promote a stronger and healthier data culture.
Overview: Our team is responsible for the continuous improvement of the lean agile operating model and delivery teams to optimize Strategic Platform Team's effectiveness of executing on agile principles with a focus on Testing, DevOps and Release Management. The team develops and tracks process performance measures, identifies and implements process requirements, drives process improvements and adoption of Best Practices.
Responsibilities
  • Develop, design, and maintain PowerBI dashboards and analytics
  • Collect, refine, and prepare data for analytics and visualization
  • Manage and utilize the PowerBI platform to extract meaningful insights from it
  • Prepare reports using various visualization and data modeling methods
  • Connecting data sources, importing data, and transforming data for Business intelligence.
  • Determines and documents data mapping rules for movement of medium to high complexity data between applications.
  • Investigates and resolves data issues across platforms and applications, including discrepancies of definition, format and function.
  • Discuss the requirements effectively with the client teams, and with internal teams.

Top Skills
  • Bachelor's degree in Computer Science, Statistics, Mathematics, or another quantitively-oriented degree
  • Minimum of Three (2) years of experience leveraging Tableau or PowerBI.
  • Minimum of Three (2) years of experience leveraging advanced SQL in a previous role.
  • Minimum of One (1) year of experience leveraging automation and ETL jobs to assist in data transformation and clean-up.
  • Minimum of One (1) year of experience using ML (machine learning), statistical predictive modeling, multivariate/regression, clustering, time series/survival analysis.
  • Preferred: Mastery of SQL and Python (NumPy, Pandas)
  • Experience working with extremely large datasets in a fast-paced, entrepreneurial and fluid environment.
  • Experience in client engagements, interpreting client's business challenges, and recommendations for business stakeholders.
  • Experience developing visualization such as reports, charts, tables, and other visual aids in support of findings.
  • Strong analytical and problem-solving skills with a demonstrable passion to dig into terabytes of data and quickly construct tools.
  • Proven excellence at formulating, understanding, and solving complex, non-routine problems.
  • Outstanding organization and presentation skills.
  • Strong written and verbal communication skills.

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