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Afternoon Data Analyst R Programming Jobs in Manchester, NH

Watts

Data Quality Analyst

Andover, MA · On-site

$24 - $30/hr

This role partners closely with cross-functional teams-including Finance, Operations, Engineering ... Support root cause analysis of data defects and recommend corrective actions * Document data ...

Watts

Data Quality Analyst

Andover, MA · On-site

$24 - $30/hr

This role partners closely with cross-functional teams-including Finance, Operations, Engineering ... Support root cause analysis of data defects and recommend corrective actions * Document data ...

Raytheon

Factory Data Analytics Engineer

Andover, MA

$116K - $139K/yr

Experience with at least one programming language (e.g., Python, Perl, C, C++, C#, Java etc ... Minitab, R, JMP, or SAS, etc. * Proven knowledge of database design and software architecture ...

CGI Inc.

Data/Cloud Software Engineer

Merrimack, NH · On-site

$117K - $140K/yr

Work with large datasets, performing data analysis and processing using Python or similar technologies. . Support data engineering workflows, including ingestion, transformation, and quality ...

Watts

Senior Financial Analyst - Data Science

Andover, MA · On-site

$86K - $107K/yr

Scope of Position This analytical and data-driven individual, as part of the Americas Finance Team ... Experience utilizing programming languages and database technologies such as Python, SQL, C++, or R.

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Manchester, NH

Afternoon Data Analyst R Programming information

See Manchester, NH salary details

$33.9K

$82.3K

$135.4K

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

As of Jul 16, 2026, the average yearly pay for afternoon data analyst r programming in Manchester, NH is $82,283.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,200.00 and $96,600.00 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.

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 popular job titles related to Afternoon Data Analyst R Programming jobs in Manchester, NH? For Afternoon Data Analyst R Programming jobs in Manchester, NH, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Manchester, NH look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Manchester, NH are:
What cities near Manchester, NH are hiring for Afternoon Data Analyst R Programming jobs? Cities near Manchester, NH with the most Afternoon Data Analyst R Programming job openings:
Afternoon Data Analyst R Programming jobs near you

Data Scientist-Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Andover, MA • On-site

$74K/yr

Other

Posted 11 days ago

Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO - DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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