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

Zantech

Data Analyst

San Antonio, TX · Remote

The Data Analyst will be primarily responsible for Data Analysis, Remote statistical analysis ... Bachelor's degree in Mathematics, Statistics, Computer Science, or related field. * 2-3 years of ...

Zantech

Data Analyst

San Antonio, TX · On-site +1

The Data Analyst will be primarily responsible for Data Analysis, Remote statistical analysis ... Bachelor's degree in Mathematics, Statistics, Computer Science, or related field. * 2-3 years of ...

DataAnnotation

Data Scientist

El Paso, TX · Remote

$40/hr

We are looking for a Data Scientist to join our team to train AI models. You will measure the ... Computer Science. Benefits This is a full-time or part-time REMOTE position You'll be able to ...

Wiser

Junior Geospatial Technician (Remote)

Denton, TX · On-site +1

$16.50/hr

Junior Geospatial Technician Entry-Level Remote Wiser Imagery Services employs personnel within the ... Performs Production efforts to include feature data, terrain, or cartographic work efforts * Tasks ...

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Data Science Entry Level Remote information

What are the key skills and qualifications needed to thrive as an entry-level remote Data Scientist, and why are they important?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What are some typical challenges entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

What are data science entry level remote jobs?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.

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

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

What are the most commonly searched types of Data Science Remote jobs in Texas? The most popular types of Data Science Remote jobs in Texas are:
What are popular job titles related to Data Science Entry Level Remote jobs in Texas? For Data Science Entry Level Remote jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Science Entry Level Remote jobs in Texas look for? The top searched job categories for Data Science Entry Level Remote jobs in Texas are:
What cities in Texas are hiring for Data Science Entry Level Remote jobs? Cities in Texas with the most Data Science Entry Level Remote job openings:
Data Science Entry Level Remote jobs near you
Political Scientist - AI Trainer

Political Scientist - AI Trainer

DataAnnotation

El Paso, TX • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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