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Afternoon Data Analyst R Programming Jobs in Michigan

Canopy

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

Join Canopy, a Ford-backed company, at the forefront of engineering advanced threat detection and ... As a Senior Data Analyst reporting to the Team Manager of Core AI and Data, you will spearhead the ...

Spectrum Health

Data Analyst Senior

Royal Oak, MI · Hybrid

$80K - $101K/yr

Performs the initial analysis of data, develops customized reports to facilitate meaningful ... Determines programming/interface needs within the department/service to DS programming staff and ...

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

$63.25 - $81.50/hr

... R Programming for data visualizations, Python, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS (SageMaker, EC2, S3), Azure (Machine Learning Studio ...

KYYBA

Warranty Data Analyst - Automotive

Auburn Hills, MI · On-site

$50 - $55/hr

... engineering, and suppliers to drive root cause analysis and corrective actions Perform deep-dive data analysis to support escalation of critical issues and leadership reporting Ensure data accuracy ...

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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 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
Dealer Audit - Data Analyst & AI Solutions

Dealer Audit - Data Analyst & AI Solutions

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 26 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

The role requires a creative and detail-oriented individual. In this role, you will develop and respond to requests for data analysis to present a coherent vision of business activities, assisting the Dealer Audit teams and key stakeholders in making data-driven decisions. The selected candidate will provide a blend of technical and functional expertise.
AI Solutions: The role drives the identification, design, pilot, and scaling of AI and automation solutions across Dealer Audit. The role works to deliver measurable impact through workflow optimization, improved customer and employee experience, and digital process transformation. This role supports the broader organizational mission to accelerate digital transformation and scale AI adoption.
Key Responsibilities
  • Analyze large and complex data sets from multiple sources to identify trends, patterns, and insights
  • Work with stakeholders to propose, identify, and develop analytics requirements
  • Build visualization or perform further analysis based on requirements identified
  • Know business data and provide recommendations for improving knowledge and data quality
  • Support audit teams in deepening their knowledge and utilization of data and AI within testing
  • Stay up-to-date with the latest advancements in AI and data analytics technologies
  • Identify high-value AI, Copilot, and other automation opportunities to embed into daily operations
  • Conduct process mapping and problem analysis to define requirements and value hypotheses
  • Translate business needs into clear user stories, requirements, and acceptance criteria
  • Partner with stakeholders to ensure feasibility and solution integration
  • Develop deployment playbooks, documentation, and training assets
  • Create reusable templates, prompt libraries, workflows, or automation components
  • Define KPIs and measure performance, productivity, and financial outcomes
  • Ensure compliance with Stellantis' Responsible AI and Data Governance frameworks

Basic Qualifications
  • Bachelor's Degree in Business, Data Science, Statistics, Business Analytics, Management Information Systems, or a related field
  • A minimum of 5 years of experience as a Data Analyst, AI Analyst, or similar role
  • Strong knowledge of data visualization tools such as PowerBI, Tableau, Qlik, or similar tools
  • Familiarity with programming languages such as Python, R, SQL, NoSQL
  • Familiarity with platforms such as Visual Studio Code, Databricks, Snowflake, Palantir Foundry
  • Strong computer skills and highly proficient with Microsoft Office Suite (O365 / Online Collaboration Version)
  • AI literacy: understanding capabilities, limitations, risks, and responsible use
  • Flexible and adaptable to changing business environments and job responsibilities
  • Excellent written and verbal communication skills in English
  • Quantitative, analytical, and detail-oriented. Problem-solving skills
  • Strong project management skills; effective & efficient completing numerous tasks simultaneously
  • Knowledge of risk management, control objectives/activities, and automated/manual controls
  • Proficiency in data collection, warehousing, transformation, and analysis

Preferred Qualifications
  • Prior audit experience (financial, compliance, operational, or dealership/franchise)
  • Experience with automotive OEM dealership management systems
  • General understanding of the franchised dealership model
  • Experience with highly automated/digital processes; including but not limited to remote auditing techniques, claims processing, and optical recognition software
  • Advanced Degree in Business, Data Science, Statistics, Business Analytics, Management Information Systems, or a related field
  • 5+ years of (total) experience in the following areas:
  • Automotive (Retail) - In-depth knowledge of dealership retail processes and procedures, with emphasis on fixed operations departments.
  • Automotive (Technical) - In-depth knowledge of automotive technical information systems and repair/diagnostic procedures

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