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Trainee Data Science Jobs in Indiana (NOW HIRING)

Office Assistant

Fort Wayne, IN

$13.75 - $18.25/hr

At every level--from management trainees to senior managers in field operations, sales, marketing ... Data entry, distribution of information, and project management * Perform other office-related work ...

Office Assistant

Fort Wayne, IN

$13.75 - $18.25/hr

At every level--from management trainees to senior managers in field operations, sales, marketing ... Data entry, distribution of information, and project management * Perform other office-related work ...

Pest Control Technician

South Bend, IN · On-site

$18.25 - $23.25/hr

As a Pest Control Technician Trainee, you'll be at the forefront of protecting public health and ... science-based solutions, data-driven insights and world-class service to advance food safety ...

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Showing results 1-20

Trainee Data Science information

See Indiana salary details

$35.7K

$116.8K

$187K

How much do trainee data science jobs pay per year?

As of Aug 6, 2026, the average yearly pay for trainee 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 are the key skills and qualifications needed to thrive as a trainee data scientist, and why are they important?

To thrive as a Trainee Data Scientist, you need a foundational understanding of statistics, programming (often Python or R), and data analysis, usually supported by a relevant degree or coursework in mathematics, computer science, or engineering. Familiarity with data visualization tools (such as Tableau or Power BI), machine learning libraries (like scikit-learn or TensorFlow), and basic database systems is often expected. Strong problem-solving skills, curiosity, and effective communication help you interpret data insights and collaborate with team members. These skills are crucial for extracting actionable insights from data and contributing meaningfully to data-driven projects.

What is the difference between Trainee Data Science vs Data Analyst?

AspectTrainee Data ScienceData Analyst
Required CredentialsBasic degree in related field, entry-level certificationsDegree in statistics, mathematics, or related field, often with certifications
Work EnvironmentInternship or entry-level role in tech or finance companiesBusiness, finance, marketing departments across industries
Employer & Industry UsageStart of data career path, training-focused rolesData-driven decision making, reporting, and analysis

In summary, a Trainee Data Science role is an entry-level position focused on learning and developing skills in data science, often as part of an internship or training program. A Data Analyst typically has more experience in analyzing data, creating reports, and supporting business decisions. Both roles are essential in data-driven industries but differ mainly in experience level and scope of responsibilities.

What does a trainee data scientist do?

A Trainee Data Scientist assists in gathering, cleaning, and analyzing data to support business decisions. They work under the guidance of senior data scientists to learn about data modeling, statistical analysis, and using tools such as Python, R, or SQL. Their responsibilities often include preparing reports, visualizing data, and contributing to the development of predictive models. The goal is to build foundational skills and gain hands-on experience in the field of data science.

What are some common challenges faced by trainee data scientists during their initial projects, and how can they overcome them?

Trainee Data Scientists often encounter challenges such as working with messy or incomplete datasets, understanding complex business problems, and selecting the appropriate modeling techniques. Collaborating closely with experienced team members and seeking feedback can help trainees navigate these obstacles. Additionally, actively participating in code reviews and knowledge-sharing sessions accelerates learning and builds confidence in tackling real-world data science tasks.
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 are popular job titles related to Trainee Data Science jobs in Indiana? For Trainee Data Science jobs in Indiana, the most frequently searched job titles are:
What cities in Indiana are hiring for Trainee Data Science jobs? Cities in Indiana with the most Trainee Data Science job openings:
Infographic showing various Trainee Data Science job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 11% Part Time, and 8% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $116,793 per year, or $56.2 per hour.

Post Doc Research Associate

Purdue University

West Lafayette, IN • On-site

Full-time

Re-posted 26 days ago


Purdue University rating

7.5

Company rating: 7.5 out of 10

Based on 136 frontline employees who took The Breakroom Quiz

308th of 615 rated colleges and universities


Job description

Post Doc Research Associate
City: West Lafayette
Job Description:
Job Summary
Position Title: Postdoctoral Research Associate - Bioinformatics, Pharmacogenomics, and AI/Machine Learning
Job Description: A Postdoctoral Research Associate position is immediately available for a highly motivated, independent, and ambitious candidate in the Department of Pharmacy Practice at Purdue University College of Pharmacy (Indianapolis campus). This position offers extensive collaborative research opportunities with the Regenstrief Institute and Indiana University. The successful candidate will work closely with faculty, scientists, clinicians, informaticians, health professionals, and trainees across institutions to develop and apply computational methods for biomedical discovery and precision therapeutics.
This position is ideal for candidates seeking advanced training and leadership opportunities in bioinformatics, pharmacogenomics, artificial intelligence, machine learning, computational drug discovery, and precision medicine.
Research Area
The postdoctoral fellow will contribute to projects in one or more of the following areas:
• Bioinformatics and computational biology
• Multi-omics data integration and analysis
• Pharmacogenomics and computational drug discovery
• Pharmacogenomics and precision medicine
• AI and machine learning applications in biomedical research
• Deep learning and predictive modeling
• Natural language processing and large language models for biomedical data
• Drug response prediction and treatment optimization
• Biomedical knowledge graphs and network medicine
• Translational data science for therapeutic discovery
Primary Responsibilities:
The Postdoctoral Research Associate is expected to lead and contribute to independent and collaborative research projects, including but not limited to:
• Developing and applying bioinformatics, pharmacogenomics, AI, machine learning, and deep learning methods
• Analyzing and integrating large-scale biomedical datasets, including omics, pharmacogenomics, medication, drug database, ontology, knowledge graph, and clinical molecular data
• Building computational pipelines for drug discovery, drug response prediction, therapeutic target identification, and precision therapeutics
• Developing predictive models, knowledge graphs, NLP/LLM applications, and AI-enabled analytic frameworks
• Leading manuscript preparation and contributing to grant proposals and scientific dissemination
• Collaborating with multidisciplinary stakeholders, including clinicians, biomedical scientists, informaticians, and data scientists
Education
Ph.D. or equivalent degree in a related field, such as bioinformatics, biomedical informatics, computer science, computational biology, biostatistics, pharmacogenomics, biomedical engineering, health data science, or a related discipline
Experience
1. Demonstrated research experience in one or more of the following areas: bioinformatics; pharmacogenomics; artificial intelligence; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine
2. Strong programming skills in Python, R, SQL, or related languages
3. Experience with omics data, pharmacogenomics data, drug databases, biomedical ontologies, knowledge graphs, or large-scale biomedical datasets is highly desirable
4. Strong written and oral communication skills, with evidence of scholarly productivity, including peer-reviewed publications or conference presentations
5. Ability to work effectively with diverse multidisciplinary teams, including clinicians, biomedical scientists, informaticians, and data scientists
Application Materials:
Interested applicants should submit the following:
1. Curriculum Vitae
2. Cover letter explaining research interests, relevant experience, and career goals
3. Contact information for 2-3 references
Internal candidates use this link https://careers.purdue.edu/job/Postdoctoral-Research-Associate/43347-en_US/?isInternalUser=true
External candidates use this link https://careers.purdue.edu/job/Post-Doc-Research-Associate/43347-en_US/

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