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Statistician Jobs in Indiana (NOW HIRING)

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Statistician information

See Indiana salary details

$48.1K

$82.7K

$110.9K

How much do statistician jobs pay per year?

As of Jul 14, 2026, the average yearly pay for statistician in Indiana is $82,711.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,700.00 and $93,700.00 per year, depending on experience, location, and employer.

Is it hard to become a statistician?

Becoming a statistician typically requires at least a bachelor's degree in statistics, mathematics, or a related field, with many roles preferring a master's degree or higher. Developing strong analytical skills, proficiency in statistical software, and gaining experience through internships or projects can also be important for entering the profession.

What do you do as a statistician?

A statistician analyzes data to identify patterns, trends, and relationships, often using statistical software and methods. They design experiments, interpret results, and communicate findings to support decision-making across various fields such as healthcare, business, and government.

What are the key skills and qualifications needed to thrive as a Statistician, and why are they important?

To thrive as a Statistician, you need strong analytical skills, a solid background in mathematics and statistics, and at least a bachelor's degree in a related field. Proficiency with statistical software such as R, SAS, Python, or SPSS and familiarity with data analysis tools are typically required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting results and conveying findings to diverse audiences. These skills ensure accurate data-driven insights and support informed decision-making in various industries.

What does a statistician do?

A statistician collects, analyzes, and interprets data to help solve real-world problems in fields such as business, healthcare, government, and science. They design surveys, experiments, or opinion polls to gather data, and then use mathematical techniques and statistical software to interpret their findings. Statisticians play a vital role in decision-making processes by providing accurate data analysis and insights, which can be used to inform policy, optimize processes, or improve products and services.

What are some common challenges statisticians face when working with large datasets, and how are these typically addressed?

Statisticians often encounter challenges such as data quality issues, missing values, and computational limitations when working with large datasets. To address these, they use data cleaning techniques, employ imputation methods for missing data, and leverage specialized statistical software or programming languages like R and Python for efficient data processing. Collaborating closely with data engineers and subject matter experts is also critical to ensure that the data is both accurate and relevant for analysis. Staying updated on best practices and new tools helps statisticians manage these challenges effectively.

What jobs make $1,000,000 a year?

For statisticians, earning $1,000,000 annually is uncommon and typically requires senior roles in large corporations, consulting firms, or finance sectors, often involving advanced skills in data analysis, modeling, and programming. High earnings may also come from entrepreneurship, executive positions, or specialized consulting with significant experience and a strong professional network.

What Do Statisticians Do?

Statisticians collect and analyze mathematical data. They interpret data and statistics and find patterns to provide insights and solutions for a wide range of industries, such as business, healthcare, agriculture, and engineering. Statisticians may work alone, or collaborate on an interdisciplinary team to tackle a particular issue.

Do statisticians make a lot of money?

Statisticians typically earn a competitive salary, with median annual wages above the national average for all occupations. Salaries vary based on experience, education, industry, and location, and advanced skills in data analysis and statistical software can lead to higher pay.
What are the most commonly searched types of Statistician jobs in Indiana? The most popular types of Statistician jobs in Indiana are:
What job categories do people searching Statistician jobs in Indiana look for? The top searched job categories for Statistician jobs in Indiana are:
What cities in Indiana are hiring for Statistician jobs? Cities in Indiana with the most Statistician job openings:
Infographic showing various Statistician job openings in Indiana as of July 2026, with employment types broken down into 85% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $82,711 per year, or $39.8 per hour.
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Muncie, IN

$74K/yr

Other

Posted 5 days ago

New


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

235th of 692 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
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 Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • 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.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, 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. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, 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.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
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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