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Trainee Data Science Jobs in Dallas, TX (NOW HIRING)

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Trainee Data Science information

See Dallas, TX salary details

$37.1K

$121.4K

$194.4K

How much do trainee data science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for trainee data science in Dallas, TX is $121,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,500.00 per year, depending on experience, location, and employer.

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 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.

Can you get into trainee data science with no experience?

Trainee data science roles often do not require prior experience and are designed for beginners. Candidates typically need foundational skills in programming, statistics, or data analysis, which can be gained through online courses or self-study. Demonstrating a willingness to learn and basic knowledge of tools like Python or Excel can improve chances of entry-level hiring.

How do I get a job in trainee data science with no experience?

To secure a trainee data science position with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, certifications, or projects can demonstrate your abilities to employers and improve your chances of entry-level roles.

What are the most commonly searched types of Data Science jobs in Dallas, TX?

The most popular types of Data Science jobs in Dallas, TX are:

What are popular job titles related to Trainee Data Science jobs in Dallas, TX?

For Trainee Data Science jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Trainee Data Science jobs in Dallas, TX look for?

The top searched job categories for Trainee Data Science jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Trainee Data Science jobs?

Cities near Dallas, TX with the most Trainee Data Science job openings:

Trainee Data Science jobs near you
Infographic showing various Trainee Data Science job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,417 per year, or $58.4 per hour.

Clinical Fellow (Non-ACGME) Research Trainee

Ctsnet, Inc.

Dallas, TX • On-site

$60 - $80/hr

Other

Posted 4 days ago

Job description

UT Southwestern/Texas Health Resources General Thoracic Surgery Research Trainee (Clinical Fellow-Non-ACGME) 1‑2 Year Clinical Fellow (Non‑ACGME) Research Trainee Program Overview

The Department of Cardiothoracic Surgery at UT Southwestern Medical Center, in partnership with Texas Health Resources, offers a 1‑2‑year non‑ACGME research track in General Thoracic Surgery. This program is intended for general surgery residents or off‑cycle candidates seeking advanced training in clinical, translational, and/or basic science research. Fellows train within the Harold C. Simmons Comprehensive Cancer Center, the only NCI‑designated Comprehensive Cancer Center in North Texas.

Institutional Strengths
  • Simmons Comprehensive Cancer Center: Integrated research programs, multidisciplinary care, and active clinical trials.
  • UT Lung Cancer SPORE: Collaboration with MD Anderson focused on precision therapies, biomarkers, and immuno‑oncology with rich research resources.
  • Advanced Imaging Research Center: Cutting‑edge MRI, CT, PET, and optical imaging platforms supporting tumor imaging and biomarker studies.
  • Metabolomics & Microbiome Programs: Research in cancer metabolism and host–microbiome interactions.
  • Outcomes & Population Research: Collaboration with the School of Public Health for health services, outcomes, and quality research.
Research Opportunities
  • Clinical: Thoracic oncology, minimally invasive surgery, perioperative care, and outcomes research.
  • Translational: Immuno‑oncology, tumor biology, biomarkers, and SPORE‑based projects.
  • Basic Science: Tumor metabolism, imaging science, and microbiology.
Education & Training

Fellows may pursue graduate coursework or degrees (e.g., M.S., M.P.H.) and receive formal training in biostatistics, epidemiology, study design, and grant writing through UT Southwestern Graduate School of Biomedical Sciences and the O’Donnell School of Public Health, contingent upon meeting admission requirements. Numerous T32 and institutional training programs provide structured didactics in biostatistics, epidemiology, study design, grant writing, and responsible conduct of research.

Mentorship & Career Development

Each fellow is supported by a thoracic surgery mentor and multidisciplinary team. The program emphasizes publications, grant development, and preparation for cardiothoracic surgery fellowship and academic careers.

Funding & Resources

Fully funded 1‑2 year position with competitive salary and benefits. Access to established research programs and shared resources in biostatistics, imaging, and data science.

Eligibility

Applicants must be general surgery residents (ACGME‑accredited or equivalent), typically PGY‑2 or PGY‑3, with demonstrated interest in academic thoracic surgery and research productivity.

Application Instructions

Submit current CV, a 1‑2 page personal statement, and 2‑3 letters of recommendation (including Program Director). In the personal statement, describe your research interests, career goals, and preferred focus (clinical, translational, and/or basic science).

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