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Data Science Jobs in Indiana (NOW HIRING)

The successful candidate will support data governance, analytics, reporting, system administration, and data science initiatives while working closely with stakeholders to develop technical solutions ...

The successful candidate will support data governance, analytics, reporting, system administration, and data science initiatives while working closely with stakeholders to develop technical solutions ...

Sr. Data Scientist

Indianapolis, IN ยท On-site

$110.21 - $121.23/hr

Contribute to spatial data infrastructure and cloud-native geospatial workflows as needed WHAT YOU BRING * 3-6 years of experience in data science, GIS, or a related field * Strong proficiency in ...

RDA > Data Science Please be advised that Elevance Health only accepts resumes for compensation from agencies that have a signed agreement with Elevance Health. Any unsolicited resumes, including ...

... a Data Scientist to provide engineering and technical support to assist our government customer ... Science and Technology (S&T) community. Products will support algorithm development on Unmanned ...

Data Scientist Location: Columbus, IN Duration: 9 weeks Primary Skills: this is a fixed fee project ... Education Requirements MINIMUM MSc in Statistics, Mathematics, Computer Science; PhD preferred ...

Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or ... more years predictive modeling experience in another industry. Education, Certifications ...

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Showing results 41-60

Data Science information

See Indiana salary details

$35.7K

$116.8K

$187K

How much do data science jobs pay per year?

As of Aug 20, 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 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 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 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.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

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:

Infographic showing various Data Science job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $116,793 per year, or $56.2 per hour.

Postdoctoral Fellow in Biostatistics & Health Data Science

Indiana University School of Medicine

Indianapolis, IN โ€ข On-site

$46K - $63K/yr

Full-time

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Postdoctoral Fellow in Biostatistics & Health Data Science

Indiana University is an equal opportunity employer and provider of ADA services and prohibits discrimination in hiring. See Indiana University's Notice of Non-Discrimination here which includes contact information.

The Annual Security and Fire Safety Report, containing policy statements, crime and fire statistics for all Indiana University campuses, is available online. You may also request a physical copy by emailing IU Public Safety at iups@iu.edu

The postdoctoral position addresses a fundamental and timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization?

We are particularly interested in:

  • LLM-driven systems for aligning real-world health data to standards like OMOPCDM, FHIR, and UMLS
  • Agent-based workflows that explain, refine, and adapt semantic mappings over time
  • Hybrid architectures that combine knowledge-grounded reasoning with flexible machine learning
  • Tools that reduce manual burden while preserving traceability and clinical interpretability

This position offers the opportunity to publish novel methods, work with real messy multi-source data, and contribute to infrastructure supporting population-level research and health equity.

The postdoctoral fellow will be based in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine, in close collaboration with the Regenstrief Institute, a nationally renowned center for health informatics research and real-world data infrastructure.

Our Team's Approach-We are not a pure research group. We operate at the interface of research and health data operations, building methods that not only publish but also deploy. We handle real clinical and public health data problems where ambiguity, variation, and scale are the normโ€”not the exception.

We welcome postdocs who want to drive innovation while engaging deeply with practical, meaningful data challenges.

Responsibilities:

  • Design and implement LLM-based methods for clinical data harmonization, semantic normalization, and ontology alignment
  • Develop multi-agent or RAG-style (retrieval-augmented generation) workflows for schema matching and terminology mapping
  • Collaborate with national and multi-institutional initiatives in data integration and standardization
  • Support open-source tooling, reproducible pipelines, and standards-based approaches (e.g., OMOP, FHIR, UMLS)
  • Lead or support manuscript preparation and dissemination at top informatics and AI venues
  • Contribute to grant development and proposal writing

What We Offer:

  • A collaborative environment at the intersection of real-world data, applied AI, and translational science
  • Opportunities to work across academic, clinical, and public health settings
  • Mentorship and support toward independent research or career development in academia or industry
  • Competitive salary and benefits through Indiana University
  • A culture that values both scientific innovation and practical impact

The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.

IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.

Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life โ€“ the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years.

For additional information on life in Indy: https://faculty.medicine.iu.edu/relocation.

The search will continue until the positions are filled.

Basic Qualifications - Required Qualifications:

  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.

Department Contact for Questions - Professor Jiang Bian via email at: bianj@regenstrief.org

Additional Qualifications - Preferred Qualifications:

  • Experience with concept normalization, ontology mapping, or schema alignment
  • Familiarity with LLM agents, tool-augmented reasoning, or hybrid rules + LLM systems
  • Record of publications in relevant domains (informatics, machine learning, AI, knowledge representation)
  • Experience with multi-site data harmonization or federated data environments

Special Instructions

Priority Application Review Deadline

Expected Start Date

Posting Number - IUSM-02358-2026

Supplemental Questions

Required fields are indicated with an asterisk (*).

  • * How did you hear about this position?
    • Personal Contact: At Professional Meeting or Conference
    • Personal Contact: Direct Contact by Search Committee
    • Personal Contact: Referred by colleague or advisor
    • Personal Contact: School of Medicine recruiter
    • Personal Contact: IUHP Physician Recruiter
    • Announcement: Other Journal or Magazine
    • Announcement: Other Website
  • * Are you a dual career partner (your partner or spouse is already being recruited)?
    • Yes
    • No

Applicant Documents

Required Documents

  • Curriculum Vitae
  • Letter of Application
  • List Of References

Optional Documents