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Computer Science Statistics Jobs in Indiana (NOW HIRING)

Master's degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science double major or Statistics/Math and ...

Master's degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science double major or Statistics/Math and ...

Bachelor's Degree in an analytical/research field (Math, Physics, Engineering, Computer Science, Statistics, etc.) and 5+ years of experience in data analytics, or equivalent combination. Advanced ...

Master's or PhD degree in Computer Science, Statistics, Bioinformatics, Mathematics or equivalent preferred. * Previous software engineering management and project management experience. * Extensive ...

Recent computer science/engineering/mathematics/statistics or science graduates or people looking to switch careers or who have had gaps in employment and looking to make their careers in the tech ...

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Computer Science Statistics information

See Indiana salary details

$35.7K

$116.8K

$187K

How much do computer science statistics jobs pay per year?

As of Jul 1, 2026, the average yearly pay for computer science statistics in Indiana is $116,793.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $129,400.00 per year, depending on experience, location, and employer.

What is the highest paying job with a statistics degree?

Data scientist roles are among the highest paying jobs for individuals with a statistics degree, often offering six-figure salaries. These positions typically require strong analytical skills, proficiency in programming languages like Python or R, and experience with machine learning and data visualization tools.

What is a Computer Science Statistics job?

A Computer Science Statistics job involves applying statistical methods and data analysis techniques to solve problems in computing, artificial intelligence, and software development. Professionals in this field work with large datasets, develop predictive models, and optimize algorithms for machine learning, cybersecurity, and data science applications. They may work in industries such as finance, healthcare, or technology, using statistical reasoning to enhance decision-making and efficiency. Strong programming skills, knowledge of probability theory, and experience with data visualization are typically required.

What jobs do most CS majors get?

Computer Science majors often pursue roles such as software developers, data analysts, systems analysts, cybersecurity specialists, and database administrators. These positions typically require programming skills, knowledge of algorithms, and familiarity with tools like Java, Python, or SQL, and often offer entry-level opportunities in tech companies, finance, healthcare, and other industries.

Is computer science dead due to AI?

Computer science remains a vital field for roles involving AI development, data analysis, and software engineering. AI advances create new opportunities for computer scientists to develop algorithms, machine learning models, and innovative technologies, making the discipline more relevant than ever.

Is statistics useful for computer science?

Statistics is highly useful for computer science, especially in data analysis, machine learning, and algorithm development. It provides essential tools for interpreting data, making predictions, and optimizing systems, which are core skills in many computer science roles.

What are the most common projects or tasks for professionals in Computer Science Statistics roles?

Professionals in Computer Science Statistics roles frequently work on projects involving data analysis, predictive modeling, and the development of algorithms to extract insights from large datasets. Their typical responsibilities include cleaning and preparing data, designing and running statistical tests, coding custom analytics solutions, and visualizing results for reports or presentations. Collaboration with teams such as data engineers, software developers, and business analysts is common to ensure that statistical models effectively address real-world business problems. This role offers opportunities to work across diverse industries, allowing for continual learning and skill development.

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

To excel in a Computer Science Statistics role, a strong background in both statistical analysis and computer science principles, usually backed by a degree in a related field, is essential. Expertise in programming languages like Python or R, experience with statistical software, and familiarity with databases or machine learning libraries are highly valued. Analytical thinking, attention to detail, and effective communication are key soft skills that differentiate top performers in this position. Mastery of these skills enables professionals to accurately interpret data, develop robust analytical solutions, and clearly convey complex findings to both technical and non-technical stakeholders.

What are popular job titles related to Computer Science Statistics jobs in Indiana? For Computer Science Statistics jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Computer Science Statistics jobs in Indiana look for? The top searched job categories for Computer Science Statistics jobs in Indiana are:
Postdoctoral Research Fellow in Sustainability and Data Science

Postdoctoral Research Fellow in Sustainability and Data Science

University of Notre Dame

Notre Dame, IN • On-site

Full-time

Posted 9 days ago


University Of Notre Dame rating

7.2

Company rating: 7.2 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

337th of 544 rated colleges and universities


Job description

Description
The University of Notre Dame invites applications for a cohort of outstanding Postdoctoral Research Fellows with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI). These fellows will join a dynamic, interdisciplinary team working at the intersection of data innovation and sustainability science, aligned with the values and principles of integral ecology.
The research fellows will contribute to a new research project that is creating a Pan-Amazon Evidence and Action Hub for socio-economic and ecological flourishing in Amazonia. The hub will systematically synthesize and harmonize remote sensing, survey, census, and citizen science data to support analyses of issues for action in partnership with local communities and Indigenous Peoples in the Amazon region. Fellows will integrate and harmonize fragmented data from diverse sources into a coherent, usable form to support novel analyses that advance key sustainability goals. The work of the Hub will generate findings to support the design and adoption of interventions that respond to changing needs of the region and its people around climate change, energy, mining, soil and water contamination, food production and livelihoods.
The postdoctoral cohort will function as a central research skills hub, supporting and elevating the sustainability-related research efforts of faculty and students across Notre Dame. The fellows will help advance impactful, solution-oriented sustainability research that engages ecological, social, economic, and ethical dimensions in an integrated manner.
The postdoctoral fellows will assume the following key responsibilities:
  • Collaborate with faculty to design, implement, and support sustainability-related research projects requiring advanced data analytics.
  • Develop and maintain a centralized platform for the Pan-Amazon Evidence and Action Hub that hosts diverse and harmonized sustainability-related datasets, including environmental, socioeconomic, cultural, and geospatial data.
  • Harmonize, curate, and provide customized datasets across multiple spatial and temporal resolutions tailored to specific research questions and stakeholder needs.
  • Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable insights.
  • Co-author and support high-impact, interdisciplinary research publications in leading sustainability and environmental science journals.
  • Engage in collaborative grant writing and proposal development to sustain and expand the cohort's research initiatives.

This search is conducted with leadership from Notre Dame's Just Transformations to Sustainability Initiative and Data, AI, and Computing Initiative, both significant investments from the Provost's Office. The Just Transformations to Sustainability Initiative is Notre Dame's University-wide effort to build a sustainable future where people and nature flourish together. The Data, AI, and Computing Initiative's core aim is to advance purposeful data, AI, and computing - excelling in foundational research while catalyzing interdisciplinary collaboration and real-world translation to address pressing societal challenges.
This is a full-time position available with an initial appointment of one-year, renewable for an additional year on the basis of satisfactory performance and availability of funding.
Qualifications
Required Qualifcations:
  • Ph.D. (in hand by the starting date) in Data Science, Computer Science, Statistics, Environmental Science, Sustainability Studies, or a related field with a strong quantitative focus. Applicants with an interdisciplinary degree are welcome.
  • Demonstrated proficiency in data management, data harmonization, and advanced data analysis techniques.
  • Strong programming skills in Python, R, and/or similar software.
  • Experience working with large and complex datasets, including geospatial and temporal data.
  • A strong publication record in data-driven sustainability research or closely related fields.
  • Excellent communication skills and an ability to work collaboratively with researchers from a wide range of disciplines.
  • Spanish language fluency or professional proficiency

Preferred Qualifications:
  • Experience working with socioeconomic data or other indicators of human wellbeing.
  • Experience working in multidisciplinary teams with researchers from diverse backgrounds.

Application Instructions
Applications will be reviewed on a rolling basis starting on November 1, 2025 and will continue until the positions are filled.
Interested applicants should submit the following materials at their earliest convenience.
  1. A cover letter that describes in detail how their research background and qualifications correspond to the position description outlined above.
  2. A detailed CV, including a list of conference presentations, publications, and research collaborations.
  3. A recent publication or dissertation chapter.
  4. Contact information for at least three references.

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