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Data Science Jobs in Indiana (NOW HIRING)

Currently pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. * Foundational knowledge of data analysis, statistics, and problem-solving techniques.

Currently pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. * Foundational knowledge of data analysis, statistics, and problem-solving techniques.

S. or further education in Mathematics, Economics, Computer Science, Statistics, or another quantitative field * 2+ years of experience as a Data Scientist, Machine Learning Engineer, or relevant ...

S. or further education in Mathematics, Economics, Computer Science, Statistics, or another quantitative field * 2+ years of experience as a Data Scientist, Machine Learning Engineer, or relevant ...

The role is responsible for providing clinical data science leadership and ownership for a particular clinical study, set of studies, or programs. Primary Responsibilities: This is intended to ...

Data Scientist Indianapolis, IN (Onsite) 12 months Contract with possibility to extension Works ... Minimally, candidates will have a bachelor's degree in statistics, math, computer science ...

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Data Science information

See Indiana salary details

$35.7K

$116.8K

$187K

How much do data science jobs pay per year?

As of May 28, 2026, the average yearly pay for data science 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 Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What are the most commonly searched types of Data Science jobs in Indiana? The most popular types of Data Science jobs in Indiana are:
What cities in Indiana are hiring for Data Science jobs? Cities in Indiana with the most Data Science job openings:
Data Scientist - Intern

Data Scientist - Intern

Dekko

Fort Wayne, IN

Full-time, Internship

Posted 2 hours ago


Job description

Job Title: Data Scientist - Intern

Location: Onsite – Fort Wayne, IN

Reports To: Director of IT

Why This Role Exists

This internship provides hands-on experience working with real-world data while exploring how AI and automation can improve business processes. You'll support data-driven decisions, help identify opportunities to streamline workflows, and contribute to building scalable reporting and automation solutions across the organization. By partnering with cross-functional teams, you'll gain exposure to the full data lifecycle and contribute to building scalable reporting and automation capabilities across the organization. By engaging with a local university student, we hope to fulfill our needs and create a relationship with future employment possibilities.

What You'll Be Doing

  • Analyze and explore data to identify trends, inefficiencies and opportunities for improvement.
  • Identify manual or repetitive processes and evaluate where automation or AI could add value.
  • Build and test simple data models, workflows, or proof-of-concepts to support business needs
  • Clean, preprocess, and organize data for analysis and usability.
  • Develop dashboards or visualizations to communicate insights clearly.
  • Partner with cross-functional teams to understand current workflows and translate business needs into practical, data-driven solutions.
  • Experiment with AI tools and emerging technologies to streamline processes and improve efficiency.
  • Document approaches, findings, and recommendations in a clear, usable way.

What You'll Bring

  • Currently pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • Foundational knowledge of data analysis, statistics, and problem-solving techniques.
  • Experience with programming (Python, R, or similar) and working with data (SQL or relational databases).
  • Interest in AI, automation, and using technology to improve how work gets done.
  • Ability to think critically about processes and identify opportunities for improvement.
  • Strong curiosity and willingness to experiment, learn quickly, and adapt in a hands-on environment.
  • Ability to communicate insights clearly to both technical and non-technical audiences.

Preferred

  • Experience with data visualization tools (e.g., Tableau, Power BI, or Cognos)
  • Previous internship or project experience in data science or analytics

How Success is Measured

  • Ability to deliver clear, accurate, and actionable insights from data.
  • Quality and reliability of models, analyses, or dashboards produced.
  • Effectiveness in communicating findings to both technical and non-technical audiences.
  • Timely completion of assigned projects and milestones.
  • Demonstrated initiative, curiosity, and willingness to learn new tools and techniques.
  • Collaboration and contribution to team goals.

Culture & Decision-Making

We value expertise and give it room to lead. Our culture emphasizes innovation, collaboration and respect for subject-matter experts.

What We'll Give You

  • Real-world experience working on impactful data projects
  • Mentorship from current IT employees
  • Opportunity to present your work to leadership
  • Networking opportunities and potential for future full-time roles

Ready to build what's next?

Apply now or reach out to learn more.

Dekko is proud to be an equal opportunity employer. We value diversity and are committed to creating an inclusive team.