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Afternoon Data Analyst R Programming Jobs in North Dakota

Reference Data Developer

Sydney, ND · On-site

$80 - $100/hr

Strong programming skills in .NET C# and or Python * Experience in Object Oriented Programming and ... Good interpersonal and communication skills for interacting with traders, quantitative analysts and ...

Digital Analyst Internships

Fargo, ND · On-site

$96K - $114K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Minot, ND · On-site

$97K - $115K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

$96K - $114K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

$98K - $116K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Bismarck, ND · On-site

$90K - $106K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Fargo, ND · On-site

$96K - $114K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Bismarck, ND · On-site

$90K - $106K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Grand Forks, ND · On-site

$94K - $111K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Grand Forks, ND · On-site

$94K - $111K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Digital Analyst Internships

Minot, ND · On-site

$97K - $115K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Collaborate with software developers, data analysts, and product teams to understand data needs * Participate in team meetings, code reviews, and brainstorming sessions * Explore opportunities to ...

$102K - $121K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

$97K - $115K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Showing results 41-60

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 the key skills and qualifications needed to thrive as an afternoon data analyst specializing in R programming?

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 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 most commonly searched types of Data Analyst R Programming jobs in North Dakota?

The most popular types of Data Analyst R Programming jobs in North Dakota are:

What are popular job titles related to Afternoon Data Analyst R Programming jobs in North Dakota?

For Afternoon Data Analyst R Programming jobs in North Dakota, the most frequently searched job titles are:

What job categories do people searching Afternoon Data Analyst R Programming jobs in North Dakota look for?

The top searched job categories for Afternoon Data Analyst R Programming jobs in North Dakota are:

What cities in North Dakota are hiring for Afternoon Data Analyst R Programming jobs?

Cities in North Dakota with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in North Dakota as of August 2026, with employment types broken down into 5% Internship, 85% Full Time, 5% Part Time, and 5% Contract. Highlights an 100% In-person job distribution.

Data Scientist (Statistician)

US Department of the Treasury

Fargo, ND • On-site

$125K/yr

Full-time

Posted 12 days ago


Key responsibilities

  • Identify, assess, and retrieve structured and unstructured data from multiple sources for data science projects.

  • Clean, transform, and integrate data, resolving issues such as missing values, outliers, and duplicates.

  • Apply data-mining processes and statistical methods to analyze data, evaluate results, and support decision-making.


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

312th of 856 rated public administrative organizations


Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

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 following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

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 closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


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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