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Computer Science Entry Level Remote Jobs in El Paso, TX

DataAnnotation

Data Science Consultant

El Paso, TX · On-site +1

$60/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

DataAnnotation

Data Scientist

El Paso, TX · Remote

$40/hr

Applied skills in Statistics and/or Computer Science. Benefits This is a full-time or part-time REMOTE position You'll be able to choose which projects you want to work on You can work on your own ...

DataAnnotation

Decision Scientist

El Paso, TX · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

DataAnnotation

Bioinformatician - AI Trainer

El Paso, TX · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

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Computer Science Entry Level Remote information

What is a Computer Science Entry Level Remote job?

A Computer Science Entry Level Remote job is a position for recent graduates or individuals with minimal experience in computer science, allowing them to work from home or another remote location. These roles often involve software development, data analysis, IT support, or QA testing. Employers typically seek candidates with programming knowledge, problem-solving skills, and familiarity with technologies like Python, Java, or SQL. Remote work requires strong communication and self-discipline to collaborate effectively with teams.

What are the key skills and qualifications needed to thrive in the Computer Science Entry Level Remote position, and why are they important?

To thrive as a Computer Science Entry Level Remote professional, you need a solid understanding of programming languages (such as Python or Java), data structures, algorithms, and a relevant bachelor's degree or equivalent coursework. Familiarity with version control systems (like Git), collaborative coding platforms, and project management tools is typically required. Strong organizational skills, proactive communication, and the ability to work independently are crucial soft skills for remote work. These abilities ensure you can deliver quality technical solutions, collaborate effectively with distributed teams, and adapt to the unique demands of a remote environment.

What are some typical challenges faced by entry-level computer science professionals working remotely?

Entry-level computer science professionals working remotely often face challenges such as managing time effectively without direct supervision, staying motivated, and overcoming feelings of isolation. Communication can also be more complex, as remote teams rely heavily on written channels and scheduled meetings to collaborate. However, most companies provide onboarding support, mentoring programs, and regular check-ins to help new hires integrate smoothly. Developing strong self-discipline and proactively reaching out to coworkers can significantly ease the transition and contribute to long-term success in a remote role.
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Computational Scientist - AI Trainer

Computational 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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