2

Entry Level Data Science Training Jobs in Texas (NOW HIRING)

Translate ambiguous business problems into structured data science statements * Organize exploratory analysis, experimentation, and research frameworks * Structure scalable ML pipelines for training ...

Translate ambiguous business problems into structured data science statements * Organize exploratory analysis, experimentation, and research frameworks * Structure scalable ML pipelines for training ...

Data Scientist

Dallas, TX · On-site

$90K/yr

Mathematics, statistics, computer science, data science or field directly related to the position ... training and experience that translates directly to paid employment. You will receive credit for ...

Translate ambiguous business problems into structured data science statements * Organize exploratory analysis, experimentation, and research frameworks * Structure scalable ML pipelines for training ...

Data Scientist

Dallas, TX · On-site

$90K/yr

Mathematics, statistics, computer science, data science or field directly related to the position ... training and experience that translates directly to paid employment. You will receive credit for ...

Data Scientist

Austin, TX · On-site

$100 - $130/hr

Act as the technical lead for data science projects focused on improving internal IT support ... and training machine learning models. * Using Tableau or Power BI to perform exploratory data ...

Data Scientist Level 3

Boerne, TX · On-site

$92K - $126K/yr

Data science * Advanced analytical algorithms * Programming (skill in at least one high-level ... 401(k) company match, training/education reimbursements and other work/life programs.

Data Scientist Level 3

San Antonio, TX · On-site

$92 - $126/hr

Data science * Advanced analytical algorithms * Programming (skill in at least one high-level ... 401(k) company match, training/education reimbursements and other work/life programs ...

Data science * Advanced analytical algorithms * Programming (skill in at least one high-level ... 401(k) company match, training/education reimbursements and other work/life programs ...

Showing results 21-40

Entry Level Data Science Training information

What is entry level data science training?

Entry level data science training is a program or course designed to introduce beginners to the fundamental concepts, tools, and techniques used in data science. These trainings typically cover topics such as data analysis, statistics, programming (often in Python or R), and the basics of machine learning. They are intended for individuals with little to no prior experience in data science and help prepare participants for entry-level roles or further study in the field.

What are the key skills and qualifications needed to thrive in entry level data science training?

To thrive in Entry Level Data Science Training, you need a solid understanding of statistics, basic programming (often Python or R), and foundational data analysis concepts, typically demonstrated through relevant coursework or a degree in a quantitative field. Familiarity with data analysis tools like Jupyter Notebooks, Excel, and introductory machine learning libraries is important, as well as exposure to version control systems like Git. Strong problem-solving skills, curiosity, and effective communication make trainees stand out in collaborative and learning-focused environments. These skills and qualities are crucial for building a successful data science career and effectively translating data insights into actionable outcomes.

What can I expect from the team structure and mentorship opportunities during entry level data science training?

During Entry Level Data Science Training, you will often find yourself working as part of a collaborative team that includes experienced data scientists, analysts, and sometimes software engineers. Many training programs and entry-level positions offer structured mentorship, where senior team members guide you through technical challenges and best practices. Regular feedback sessions and pair programming are common, helping you quickly build practical skills. You'll also likely participate in group projects, fostering teamwork and exposing you to real-world data problems.

What is the difference between Entry Level Data Science Training vs Data Analyst?

AspectEntry Level Data Science TrainingData Analyst
Required CredentialsBasic understanding of statistics, programming, and data tools; often includes certifications or coursesTypically requires a degree in statistics, mathematics, or related field; may include certifications
Work EnvironmentTraining programs, online courses, workshops; often self-paced or instructor-ledOffice setting, working with data visualization, reporting tools, and databases
Employer & Industry UsageUsed by individuals seeking entry into data science roles; employers value foundational skillsEmployed across industries for data reporting, analysis, and business insights

Entry Level Data Science Training provides foundational skills and certifications to prepare individuals for data analysis roles. Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While training emphasizes learning tools and techniques, data analysts apply these skills in real-world work environments. Both roles are essential in data-driven industries, but training is a stepping stone toward a full data analyst position.

What are the most commonly searched types of Data Science Training jobs in Texas?

The most popular types of Data Science Training jobs in Texas are:

Infographic showing various Entry Level Data Science Training job openings in Texas as of July 2026, with employment types broken down into 60% Full Time, and 40% Part Time. Highlights an 100% In-person job distribution.

$49K/yr

Full-time, Part-time

Re-posted 11 days ago


Job description

The PALACE Acquire Program offers you a permanent position upon completion of your formal training plan. As a Palace Acquire Intern you will experience both personal and professional growth while dealing effectively and ethically with change, complexity, and problem solving. The program offers a 3-year formal training plan with yearly salary increases. Promotions and salary increases are based upon your successful performance and supervisory approval.Qualifications:BASIC REQUIREMENT OR INDIVIDUAL OCCUPATIONAL REQUIREMENT:
Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
You may qualify if you meet one of the following:
1. GS-7: You must have completed or will complete a 4-year course of study leading to a bachelor's from an accredited institution AND must have documented Superior Academic Achievement (SAA) at the undergraduate level in the following:
a) Grade Point Average 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum.
2. GS-9: You must have completed 2 years of progressively higher-level graduate education leading to a master's degree or equivalent graduate degree:
a) Grade Point Average - 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum. If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP, CCAF, DANTES, military credit, etc. you cannot qualify based on GPA.
KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas:
1. Professional knowledge of basic principles, concepts, and practices of data science to apply scientific methods and techniques to analyze systems, processes, and/or operational problems and procedures.
2. Knowledge of mathematics and analysis to perform minor phases of a larger assignment and prepare reports, documentation, and correspondence to communicate factual and procedural information clearly.
3. Skill in applying basic principles, concepts, and practices of the occupation sufficient to perform routine to difficult but well precedented assignments in data science analysis.
4. Ability to analyze, interpret, and apply data science rules and procedures in a variety of situations and recommend solutions to senior analysts.
5. Ability to analyze problems to identify significant factors, gather pertinent data, and recognize solutions.
6. Ability to plan and organize work and confer with co-workers effectively.
PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work. You must clearly identify the duties and responsibilities in each position held and the total number of hours per week.
VOLUNTEER WORK EXPERIENCE: Refers to paid and unpaid experience, including volunteer work done through National Service Programs (i.e., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community; student and social). Volunteer work helps build critical competencies, knowledge and skills that can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:IF USING EDUCATION TO QUALIFY: If position has a positive degree requirement or education forms the basis for qualifications, you MUST submit transcriptswith the application. Official transcripts are not required at the time of application; however, if position has a positive degree requirement, qualifying based on education alone or in combination with experience, transcripts must be verified prior to appointment. An accrediting institution recognized by the U.S. Department of Education must accredit education. Click here to check accreditation.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying.Employment Type: OTHER