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Applied Data Science Jobs in Indiana (NOW HIRING)

Cisco

Applied AI Scientist

Indianapolis, IN

Collaborate with engineering, product, and data science teams to understand requirements, incorporate stakeholder feedback, and deliver AI/ML solutions that address business and technical needs.

New

CACI International, Inc.

Data Scientist

Crane, IN · On-site

... Science and Technology (S&T) community. Products will support algorithm development on Unmanned ... Applied Artificial Intelligence/Machine Learning (AI/ML) for image processing. * Experience with ...

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$24.4K

$138K

$210K

How much do applied data science jobs pay per year?

As of Jul 14, 2026, the average yearly pay for applied data science in Indiana is $138,036.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,461.00 and $171,550.00 per year, depending on experience, location, and employer.

What are the typical responsibilities of an Applied Data Science professional on a day-to-day basis?

An Applied Data Science professional typically spends their days gathering, cleaning, and analyzing structured and unstructured data to uncover patterns and generate actionable insights. They frequently build and deploy predictive models, collaborate with business and engineering teams to define project requirements, and communicate findings through clear reports or visualizations. Additionally, they often engage in regular team meetings, contribute to ongoing process improvements, and continuously learn new technologies or methodologies to enhance project outcomes. This combination of technical and collaborative work makes the role both dynamic and highly impactful within most organizations.

Is data science high paying?

Data science is generally considered a high-paying field, with salaries often above average for technology roles. Factors such as experience, skills in programming and statistical analysis, and industry can influence compensation levels.

What can you do with an applied data science degree?

An applied data science degree prepares individuals for roles such as data analyst, data scientist, machine learning engineer, or business intelligence analyst. Graduates can work in industries like finance, healthcare, technology, and marketing, utilizing skills in programming, statistical analysis, and data visualization tools. The degree often requires proficiency in programming languages like Python or R and knowledge of data management and modeling techniques.

What jobs can I get with applied science?

Applied Data Science prepares individuals for roles such as data analyst, data scientist, machine learning engineer, and business intelligence analyst. These jobs typically require skills in programming, statistical analysis, and data visualization tools like Python, R, or SQL, and often involve working with large datasets to inform decision-making.

What are the key skills and qualifications needed to thrive in the Applied Data Science position, and why are they important?

To thrive in Applied Data Science, you need a strong background in statistics, machine learning, data analysis, and programming languages such as Python or R, typically evidenced by a degree in a quantitative field. Familiarity with data visualization tools (like Tableau), cloud platforms (AWS, GCP), and certifications in data science or analytics are highly valued. Effective communication, problem-solving, and teamwork are crucial soft skills to convey insights and collaborate with both technical and non-technical stakeholders. These competencies are critical for transforming complex data into actionable business strategies and driving measurable impact within organizations.

Is 40 too late for data science?

Applied Data Science is a field open to individuals of various ages, and starting a career at 40 is possible with relevant skills such as programming, statistics, and data analysis. Many professionals transition into data science later in their careers by gaining certifications, building portfolios, and continuously learning new tools like Python or R.

What is an Applied Data Science job?

An Applied Data Science job focuses on using data science techniques to solve real-world problems in business, healthcare, finance, and other industries. It involves collecting, processing, analyzing, and interpreting large datasets to extract meaningful insights. Applied data scientists use machine learning, statistical modeling, and programming skills to develop data-driven solutions. They work closely with stakeholders to implement models that drive decision-making and improve operations.

What are popular job titles related to Applied Data Science jobs in Indiana? For Applied Data Science jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Applied Data Science jobs in Indiana look for? The top searched job categories for Applied Data Science jobs in Indiana are:
What cities in Indiana are hiring for Applied Data Science jobs? Cities in Indiana with the most Applied Data Science job openings:
Applied Data Science jobs near you
Infographic showing various Applied Data Science job openings in Indiana as of July 2026, with employment types broken down into 74% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $138,036 per year, or $66.4 per hour.

Data Scientist-Direct Hire-6-Month Register

Criminal Investigation & Law Enforcement | IRS Careers

Bloomington, IN • On-site

$125K/yr

Other

Posted 13 days ago

Job description

WHAT IS DATA AND ANALYTICS (DA)-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 REQUIRMENTS: 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: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
AND
SPECIALIZED EXPERIENCE GRADE 14: 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-13 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Leading data science or statistical analysis initiatives by defining project scope, analytic approach, data requirements, schedules, deliverables, or success measures; coordinating work across data, program, business, or technology stakeholders; and developing findings or recommendations for program or operational decisions.
  • Developing or applying statistical, machine learning, operations research, artificial intelligence, 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, neural networks or deep learning, or exploratory data analysis.
  • Overseeing data preparation, data quality, data governance, data certification, or analytic product delivery using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or decision-support products.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Advising managers or senior leaders on data science findings, automation opportunities, policy or program impacts, resource implications, risks, or recommended changes to processes, procedures, or operations.
  • Providing technical guidance, review, or mentoring to analysts or data scientists and preparing technical reports, briefings, presentations, or documentation that explain methods, assumptions, limitations, validation results, success measures, key performance indicators, or recommendations.
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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