Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
New
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
New
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
New
Experience may have been gained in the public sector, private sector or through Volunteer Service ... Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing ...
New
Data Scientist Volunteer information
What is a data scientist volunteer?
A Data Scientist Volunteer is an unpaid role where individuals apply data science skills, such as data analysis, machine learning, and statistical modeling, to support organizations. These volunteers often work with nonprofits, research institutions, or startups to analyze data, create insights, and support decision-making. It’s a great way to gain experience, contribute to meaningful projects, and build a portfolio while helping a cause.
What types of projects do data scientist volunteers typically work on, and how do they collaborate with other team members?
Data Scientist Volunteers often contribute to projects such as analyzing trends in nonprofit impact data, building predictive models for resource allocation, or creating dashboards to help organizations visualize their results. They usually work closely with program managers, IT staff, and other volunteers to understand data needs and deliver solutions that are aligned with organizational goals. Communication and collaboration are key, as volunteers frequently need to explain data-driven insights to team members who may not have technical backgrounds. As a volunteer, you can expect to gain practical experience on cross-functional teams, tackling real-world challenges while making a meaningful impact.
What are the key skills and qualifications needed to thrive in the data scientist volunteer position, and why are they important?
To thrive as a Data Scientist Volunteer, you need a solid grounding in statistics, mathematics, and data analysis, often supported by a relevant degree or coursework. Familiarity with tools like Python, R, SQL, and experience with data visualization software and machine learning libraries is typical, while certifications in data science or analytics can be advantageous. Strong communication, teamwork, and problem-solving abilities set you apart, especially when working within diverse or resource-limited teams. These skills are crucial for effectively deriving insights from data and delivering actionable solutions that support an organization's mission.
What are the most commonly searched types of Data Scientist jobs in Indiana?
The most popular types of Data Scientist jobs in Indiana are:
What are popular job titles related to Data Scientist Volunteer jobs in Indiana?
For Data Scientist Volunteer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Scientist Volunteer jobs in Indiana look for?
The top searched job categories for Data Scientist Volunteer jobs in Indiana are:
What cities in Indiana are hiring for Data Scientist Volunteer jobs?
Cities in Indiana with the most Data Scientist Volunteer job openings:

Data Scientist (Statistician)
Indianapolis, IN
8.2
Based on 13 frontline employees who took The Breakroom Quiz
311th of 853 rated public administrative organizations
Good employer
Paid breaks
Respectful managers
$125K/yr
Full-time
Posted 5 days ago
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.
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
About US Department of the Treasury
Sourced by ZipRecruiter
Industry
Public administration
Company size
10,000+ Employees
Headquarters location
Washington, DC, US
Year founded
1789
Website
What U.S. Department Of The Treasury employees say
Pay
Hours and flexibility
Workplace
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