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Entry Level Data Science Jobs in Allen, TX (NOW HIRING)

Synergie Systems

Entry Level Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Job Title: Entry Level Data Engineer Location: Dallas, TX Job Type: Only W2 We are looking for an ... Collaborate with Data Analysts, Data Scientists, Software Engineers, and other stakeholders.

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How much do entry level data science jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for entry level data science in Allen, TX is $17.72, according to ZipRecruiter salary data. Most workers in this role earn between $15.00 and $19.90 per hour, depending on experience, location, and employer.

What is an entry level data scientist?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

What types of projects or tasks can I expect to work on as an entry level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

What are the key skills and qualifications needed to thrive as an entry level data scientist, and why are they important?

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

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

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Are there entry-level data science roles?

Yes, entry-level data science roles are available and typically require foundational skills in programming, statistics, and data analysis, often using tools like Python or R. These positions are suitable for recent graduates or those transitioning into data science and may involve internships or junior analyst roles to gain experience.

How to start a career in entry level data science with no experience?

To start a career in entry level data science 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, earning certifications, and working on personal projects or internships can demonstrate your abilities to employers and help you gain practical experience.

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

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

What are popular job titles related to Entry Level Data Science jobs in Allen, TX?

For Entry Level Data Science jobs in Allen, TX, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Science jobs in Allen, TX look for?

The top searched job categories for Entry Level Data Science jobs in Allen, TX are:

What cities near Allen, TX are hiring for Entry Level Data Science jobs?

Cities near Allen, TX with the most Entry Level Data Science job openings:

Entry Level Data Science jobs near you
Infographic showing various Entry Level Data Science job openings in Allen, 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 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $36,862 per year, or $17.7 per hour.

Entry Level Data Engineer

Synergie Systems

Dallas, TX • On-site

$113K - $136K/yr

Other

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Job description

Job Title: Entry Level Data Engineer

Location: Dallas, TX

Job Type: Only W2

Job Description:

We are looking for an enthusiastic and detail-oriented Entry-Level Data Engineer to join our data team. You will work with experienced data engineers and analysts to build, maintain, and improve data pipelines and data infrastructure.

This is a great opportunity for someone who has a strong foundation in SQL and Python and wants to develop their career in data engineering.

Responsibilities:

Develop and maintain ETL/ELT data pipelines.

Extract, transform, and load data from databases, APIs, files, and other sources.

Write and optimize SQL queries for data processing and analysis.

Use Python to automate data-processing and engineering tasks.

Perform data validation, quality checks, and troubleshooting.

Work with relational and cloud databases.

Assist in building and maintaining data warehouses and data lakes.

Monitor data pipelines and investigate data-quality or pipeline issues.

Collaborate with Data Analysts, Data Scientists, Software Engineers, and other stakeholders.

Document data pipelines, processes, and technical solutions.

Follow best practices for data security, reliability, and scalability.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Engineering, Data Science, or a related field, or equivalent practical experience.

Strong knowledge of SQL.

Basic to intermediate Python programming skills.

Understanding of relational databases and database concepts.

Basic understanding of ETL/ELT concepts and data pipelines.

Familiarity with Git/version control.

Good problem-solving and analytical skills.

Strong communication and willingness to learn.

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