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Afternoon Data Analyst R Programming Jobs in Detroit, MI

United IT Solutions

Data Quality Analyst

Pontiac, MI · On-site

The Data Quality Analyst will support the definition of data quality standards, requirements, and ... Python, R is a plus) Skills Problem solving Issue resolution Decision-making Able to synthesize ...

OpTech

Data Science Analyst (VB/SQL)

Detroit, MI · Remote

Data Science Analyst Why work at OpTech? OpTech is a woman-owned company that values your ideas ... Include: • Knowledge of Benefit Design (Certificates and Riders) • Additional programming ...

Tech Tammina LLC

Data Scientists Modeling

Dearborn, MI · On-site

... analysis results and model insights into clear, business-oriented solutions. • Proficiency in at least one major programming language used in data science (e.g., Python, R). Skills Preferred: • ...

Contact Government Services, LLC

Data Engineer

Detroit, MI

$113K - $136K/yr

... R, SQL, SAS). -Strong knowledge of big data analysis and storage tools and technologies. -Strong understanding of the agile principles and ability to apply them. -Strong understanding of the CI/CD ...

Contact Government Services, LLC

Data Engineer

Detroit, MI

$113K - $136K/yr

... R, SQL, SAS). -Strong knowledge of big data analysis and storage tools and technologies. -Strong understanding of the agile principles and ability to apply them. -Strong understanding of the CI/CD ...

Contact Government Services LLC

Data Engineer

Detroit, MI · On-site

$104K - $125K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Proficiency to manipulate data (Python, R, SQL, SAS). * Strong knowledge of big data analysis and ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Detroit, MI

Afternoon Data Analyst R Programming information

See Detroit, MI salary details

$33.7K

$81.8K

$134.6K

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

As of Jun 10, 2026, the average yearly pay for afternoon data analyst r programming in Detroit, MI is $81,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $96,000.00 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 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.

Is data science dead in 10 years?

Data science, including roles like an Afternoon Data Analyst using R programming, is expected to remain relevant as organizations continue to rely on data-driven decision making. Advances in automation and AI may change specific tasks, but skills in data analysis, statistical methods, and programming will continue to be valuable in the foreseeable future.

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 Detroit, MI? The most popular types of Data Analyst R Programming jobs in Detroit, MI are:
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What job categories do people searching Afternoon Data Analyst R Programming jobs in Detroit, MI look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Detroit, MI are:
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Afternoon Data Analyst R Programming jobs near you

Data Quality Analyst

United IT Solutions

Pontiac, MI • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

The Data Quality Analyst will support the definition of data quality standards, requirements, and specifications for data quality controls in the data lifecycle. They will also provide support for operational processes that measure, monitor and report on data quality levels as well as the remediation of identified data quality issues.
The person will meet with various stakeholders to gather and document information, perform data analysis, and conduct assessments of business and technical processes involved in managing data.
Responsibilities
Data Quality Remediation Collaborate with internal stakeholders to gather information and document identified data quality issues. Perform root cause analysis of identified data quality issues. Collaborate with cross-functional teams to support development and implementation of remediation plans to promptly resolve identified data quality issues. Data Quality Measurement, Monitoring and Reporting Processes Define and develop data quality metrics based upon data quality standards. Support the development of automated data quality reports and dashboards. In partnership with Data Stewards, monitor data quality levels and respond to alerts when data quality metrics for critical data elements are outside the acceptable data quality thresholds. Data Quality Management Framework Collaborate with business stakeholders to identify business needs and opportunities for data quality improvement, including identifying data critical to meeting business needs. Perform an assessment of the data to understand data content and relationships and comparing actual data to rules and expectation. Develop standards and templates for documenting data quality rules so they have a consistent format and meaning.
Experience
5 years experience in data and/or information asset quality management 3 years experience managing data quality monitoring and remediation processes Proficiency in data profiling, statistical analysis, data analysis, and data standardization / cleansing techniques Experience using statistical techniques to discover the root cause of data quality issues and recommend remediation options Strong SQL skills with the ability to write sophisticated queriers across large, complex data sets Ability to analyze data trends, identify patterns and proactively address potential data quality issues Proficient in documenting data quality issues and remediation plans in a clear and concise manner Experience with Collibra, Informatica, and Snowflake (Python, R is a plus)
Skills
Problem solving Issue resolution Decision-making Able to synthesize information leading to recommendations of solutions Communication across all levels - written and verbal Attention to detail with ability to align with the big picture Multi-tasking Influencing others Challenging professionally Relationship management

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