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Data Scientist Research Associate Jobs in Iowa (NOW HIRING)

Research new analytical, visualization, automation, and AI methodologies in collaboration with data science, engineering, agronomy, UX, and product subject matter experts. * Apply data science and ...

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Data Scientist Research Associate information

What is a data scientist research associate?

A Data Scientist Research Associate is a professional who applies statistical analysis, machine learning, and data management techniques to conduct research and extract insights from complex datasets. They often work in academic, government, or industry research settings, supporting projects by designing experiments, analyzing large volumes of data, and interpreting results. Their work helps inform decision-making, advance scientific knowledge, and develop new data-driven solutions. Typically, they collaborate with multidisciplinary teams and may contribute to publishing research findings.

What are the key skills and qualifications needed to thrive as a data scientist research associate?

To thrive as a Data Scientist Research Associate, you need a solid background in statistics, machine learning, and data analysis, generally supported by a degree in computer science, statistics, or a related field. Familiarity with programming languages such as Python or R, experience with data visualization tools, and knowledge of platforms like SQL and TensorFlow are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are crucial for generating actionable insights from data and advancing research objectives.

What are some typical challenges faced by data scientist research associates when working on interdisciplinary projects?

Data Scientist Research Associates often collaborate with experts from fields such as engineering, biology, or social sciences. A common challenge is bridging the communication gap between disciplines, as each may have its own jargon and methodologies. Additionally, integrating and preprocessing diverse datasets can be complex due to varying data formats and quality. Overcoming these challenges requires strong communication skills, adaptability, and a willingness to learn about domain-specific concepts to ensure productive teamwork and successful project outcomes.

What are popular job titles related to Data Scientist Research Associate jobs in Iowa?

For Data Scientist Research Associate jobs in Iowa, the most frequently searched job titles are:

What job categories do people searching Data Scientist Research Associate jobs in Iowa look for?

The top searched job categories for Data Scientist Research Associate jobs in Iowa are:

What cities in Iowa are hiring for Data Scientist Research Associate jobs?

Cities in Iowa with the most Data Scientist Research Associate job openings:

Infographic showing various Data Scientist Research Associate job openings in Iowa as of August 2026, with employment types broken down into 69% Full Time, 12% Part Time, and 19% Contract. Highlights an 95% In-person, and 5% Remote job distribution.

$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 models and statistical methods to analyze data, evaluate results, and support decision-making.


Internal Revenue Service rating

7.4

Company rating: 7.4 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

159th of 297 rated public sector bodies


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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