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Afternoon Data Analyst R Programming Jobs in Michigan

Varsity Tutors

Data Science Tutor

Kalamazoo, MI · Remote

$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

Detroit, MI · Remote

$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 ...

THOMSON REUTERS

Customer Data Analyst

Ann Arbor, MI · Hybrid

Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to ... with the data, intelligence, and solutions needed to make informed decisions, and to help ...

Varsity Tutors

Data Science Tutor

Ann Arbor, MI · Remote

$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 ...

Epitec

Data Engineer

Southfield, MI · On-site

$114K/yr

Data Engineer (Job Code: 1391) Duties : Responsible for supporting vehicle feature level ... analysis of data collected from real-world evaluation drives; work with vehicle feature and ...

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

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

Senior Data Analyst (HYBRID Worcester, MA or Howell, MI)

thg

Howell, MI • Hybrid

$80K - $101K/yr

Other

Posted 6 days ago

Job description

Our Personal Lines State Management team is currently seeking an Senior Data Analyst in our Worcester, MA or Howell, MI location. Position is eligible for Hybrid/Flex work arrangement. This is a full-time, exempt role.

POSITION OVERVIEW:

The Senior Analytics Consultant plays a critical role in leveraging data, analytics, and business insight to influence strategic decisionmaking and drive positive business outcomes across Personal Lines. This position partners closely with business leaders, agent partners, and technical teams to translate complex data into actionable insight, develop proprietary analytical tools, and optimize performance aligned to the organization’s unique distribution and operating model.

This role requires a blend of strong analytical and technical capabilities, deep insurance expertise, and the ability to effectively communicate, influence, and lead through data. The Senior Analytics Consultant operates with significant autonomy, bringing innovative thinking and creative problemsolving to complex business challenges.

IN THIS ROLE YOU WILL:

  • Lead the development, enhancement, and execution of advanced analytics, reporting, and datadriven tools supporting Personal Lines growth, profitability, and operational efficiency.
  • Apply statistical methods, business intelligence techniques, and iterative data exploration to uncover trends, performance drivers, and opportunities for improvement.
  • Design and maintain proprietary analytical tools and processes that serve as strategic differentiators, enabling agent optimization and business consolidation.
  • Partner with business stakeholders to identify key questions or problems, translate them into analytical approaches, and deliver clear, actionable insights.
  • Influence decisionmaking by synthesizing complex data into compelling narratives tailored to executive, technical, and external audiences.
  • Serve as a core analytics contributor and project lead on initiatives of large scope and moderate to high complexity, spanning multiple products, departments, or lines of business.
  • Collaborate with technical resources (data engineering, IT, PBI teams) to ensure scalable, reliable analytics solutions.
  • Take projects endtoend—from conception and requirements gathering through delivery, evaluation, and refinement—ensuring alignment with business objectives.
  • Monitor progress, evaluate results against success metrics, and make datadriven recommendations to optimize outcomes.
  • Communicate effectively with internal partners and external agent stakeholders, building trust and credibility through insightdriven dialogue.
  • Mentor and train lessexperienced analytics team members, elevating technical proficiency and analytical thinking across the organization.

WHAT YOU NEED TO APPLY:   

  • 6 plus years professional experience and bachelor’s degree. 
  • Applied Data Science, Data Science, Information and Data Science, Information
  • Management Analytics, Data Mining, Predictive Analytics are most sought-after.   
  • Degrees in Statistics, Mathematics, Computer Science, and Information Systems are also preferred.

TECHNICAL SKILLS:

  • SQL, R, Python
  • Statistical procedures & methods
  • Strategic and Critical thinker
  • Consultative
  • Problem solver, Visionary, Inquisitive
  • Good communicator, voracious learner, naturally curious

Apply