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Trainee Data Science Jobs in Missouri (NOW HIRING)

Saint Louis University

Post Doctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

... trainees in computational methods (optional, depending on interest) Required Qualifications * PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related ...

Saint Louis University

Post Doctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

... trainees in computational methods (optional, depending on interest) Required Qualifications * PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related ...

Brightli

Student Trainee (CSS)

Saint Louis, MO

Contribute to program quality improvement efforts through participation in data collection ... Applied Science in Behavioral Health Support from an approved institution; or Four (4) years of ...

Brightli

Student Trainee (CSS)

Saint Louis, MO · On-site

... data collection, evaluation, and reporting initiatives. • Maintain collaborative working ... Science in Behavioral Health Support from an approved institution; or • Four (4) years of ...

University of Rochester

$77K - $116K/yr

TRAINING AND ADMINSTRATIVE DUTIES Provide statistical guidance to trainees and faculty. Work with ... Master's or Advanced Degree (PhD in Biostatistics, Statistics, Data Science, or a related ...

Washington University of St. Louis

... data analysis, and dissemination. PRIME-KS (NIH U01): A multi-site implementation science study ... Developed competency in mentoring junior researchers, including Kenyan trainees. There may also be ...

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Trainee Data Science information

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 Missouri? The most popular types of Data Science jobs in Missouri are:
What are popular job titles related to Trainee Data Science jobs in Missouri? For Trainee Data Science jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Trainee Data Science jobs in Missouri look for? The top searched job categories for Trainee Data Science jobs in Missouri are:
Trainee Data Science jobs near you
Infographic showing various Trainee Data Science job openings in Missouri as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Post Doctoral Fellow

Post Doctoral Fellow

Saint Louis University

Saint Louis, MO • On-site

$47K - $64K/yr

Full-time

Posted 19 days ago

Saint Louis University rating

8.9

Company rating: 8.9 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

35th of 612 rated colleges and universities

Job description

Who is Saint Louis University? Founded in 1818, Saint Louis University is one of the nation's oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service.
Postdoctoral Fellow - Computational Biology / Bioinformatics
Focus: Multi-omics and Longitudinal Modeling in Alzheimer's Disease
Appointment: Full-time, 1-year term (renewable pending funding and performance)
Position Overview
We are seeking a highly motivated Postdoctoral Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative field to join an interdisciplinary research program focused on Alzheimer's disease (AD) and neurodegeneration.
The fellow will lead and contribute to advanced bioinformatics, multi-omics integration, and statistical modeling efforts using large, well-phenotyped longitudinal datasets (e.g., proteomics, transcriptomics, imaging, clinical, and biomarker data). The position is ideal for a candidate interested in mechanistic discovery, biomarker development, and translational neuroscience, with opportunities for high-impact publications and grant development.
Key Responsibilities
  • Perform computational analysis of large-scale omics datasets, including proteomics, transcriptomics, and related modalities
  • Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts
  • Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis, dimensionality reduction, clustering, trajectory modeling)
  • Lead reproducible analysis pipelines in R, Python, or related frameworks
  • Interpret results in biological and clinical context, with emphasis on Alzheimer's disease mechanisms and biomarkers
  • Prepare figures, tables, and methods for peer-reviewed manuscripts and conference presentations
  • Collaborate with clinicians, wet-lab scientists, and biostatisticians in an interdisciplinary environment
  • Contribute to grant proposals and progress reports as appropriate
  • Mentor graduate or undergraduate trainees in computational methods (optional, depending on interest)

Required Qualifications
  • PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related quantitative discipline
  • Strong experience with high-dimensional biological data analysis
  • Proficiency in R and/or Python for statistical computing and data analysis
  • Solid foundation in statistics and data modeling, particularly for longitudinal or cohort-based data
  • Demonstrated ability to work independently and manage complex datasets
  • Strong written and verbal communication skills in English
  • Evidence of productivity (e.g., peer-reviewed publications, preprints, or advanced projects)

Preferred Qualifications
  • Experience with longitudinal modeling (e.g., mixed-effects models, disease progression modeling)
  • Familiarity with neurodegenerative disease research, Alzheimer's disease, or aging biology
  • Experience with proteomics platforms (e.g., Olink, SomaScan, mass spectrometry)
  • Knowledge of multi-omics integration, network analysis, or pathway enrichment methods
  • Experience working with large consortium datasets (e.g., ADNI, AMP-AD, UK Biobank, similar)
  • Interest in translational research, biomarker discovery, or drug target identification
  • Experience with reproducible research practices (version control, documentation, workflow tools)

Environment & Opportunities
The fellow will join a highly collaborative research environment at the interface of neurology, neuroscience, and computational biology, with access to rich datasets and strong clinical context. The position offers:
  • Intellectual ownership of projects
  • Opportunities for first-author publications
  • Exposure to grant writing and translational research strategy
  • Career mentorship tailored to academic, industry, or hybrid career paths

Term & Compensation
  • One-year appointment with possibility of renewal based on funding and performance
  • Competitive salary and benefits commensurate with experience and institutional guidelines

Application Instructions:
Applicants should submit:
1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2-3 references
Grant-funded Post-Doctoral appointments may be terminated if grant funding ends.
This position does not currently sponsor J1, H1B, or O visas.
Function
Research Support
Scheduled Weekly Hours:
40
Saint Louis University is an equal opportunity/affirmative action employer. All qualified candidates will receive consideration for the position applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed for completing the application and/or with the interviewing process, please contact Human Resources at 314-977-5847.

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