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Data Science Remote Internship Jobs in Houston, TX

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Lead Modeling Scientist Location : Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is responsible for building and scaling the data and computational backbone ...

HealthCorps

Monitoring & Evaluation Intern

Houston, TX · Remote

This internship provides an excellent opportunity for undergraduate or graduate students looking to ... Current undergraduate or graduate student studying public health, data science, social sciences, or ...

Chevron

2026-2027 Earth Science Intern

Houston, TX · On-site +1

$10K/mo

... data scientists, and/or software developers. Earth Scientists develop technical skills in ... Interns will be provided guidance by a supervisor and a technical mentor. We encourage the ...

Insolation Technology Ltd

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Bachelors degree in Data Science, Statistics, Mathematics, Engineering, or a related field ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

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Data Science Remote Internship information

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How much do data science remote internship jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for data science remote internship in Houston, TX is $21.49, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $23.41 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data science remote intern?

To thrive as a Data Science Remote Intern, you need a solid understanding of statistics, data analysis, and programming languages like Python or R, often supported by coursework or projects in data science or related fields. Familiarity with tools such as Jupyter Notebook, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow) is typically expected. Strong problem-solving abilities, self-motivation, and effective communication are essential soft skills for collaborating remotely and conveying analytical insights. These competencies ensure you can independently contribute to projects, adapt to remote workflows, and deliver actionable data-driven solutions.

What is a data science remote internship?

A Data Science Remote Internship is a temporary, practical work experience opportunity in the field of data science that is completed remotely, usually from your own home or any location with internet access. Interns work on real-world projects involving data analysis, machine learning, and statistical modeling, often collaborating with teams through online communication tools. This type of internship is ideal for gaining hands-on experience, building a portfolio, and developing skills relevant to data science careers, all while offering flexibility and eliminating the need to relocate.

What is the difference between Data Science Remote Internship vs Data Analyst Remote Internship?

AspectData Science Remote InternshipData Analyst Remote Internship
Required CredentialsTypically pursuing or recent graduate in Data Science, Statistics, or related fieldsOften pursuing or recent graduate in Data Analysis, Business, or related fields
Work EnvironmentRemote, collaborative with data science teams, using programming languages like Python or RRemote, focusing on data interpretation, visualization, and reporting tools like Excel, SQL, Tableau
Employer & Industry UsageTech companies, finance, healthcare, startupsBusiness, marketing, finance, consulting firms

While both roles involve working with data remotely, Data Science Remote Internships focus on building predictive models and programming skills, whereas Data Analyst Remote Internships emphasize data interpretation, visualization, and reporting. The choice depends on your career goals and skill set.

What types of projects can I expect to work on during a remote data science internship, and how is project collaboration typically managed?

During a remote data science internship, you can expect to work on projects such as data cleaning, exploratory data analysis, model development, and visualization tasks that support ongoing business needs. Collaboration is commonly managed through virtual tools like Slack, Zoom, and project management platforms (e.g., Jira or Trello), with regular check-ins and code reviews from your mentor or team. Interns often participate in team meetings, contribute to group presentations, and use version control systems like Git to share code and receive feedback. This structure ensures you gain practical experience while staying connected with your team, even in a remote setting.
What are popular job titles related to Data Science Remote Internship jobs in Houston, TX? For Data Science Remote Internship jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Data Science Remote Internship jobs in Houston, TX look for? The top searched job categories for Data Science Remote Internship jobs in Houston, TX are:
What cities near Houston, TX are hiring for Data Science Remote Internship jobs? Cities near Houston, TX with the most Data Science Remote Internship job openings:
Data Science Remote Internship jobs near you
Infographic showing various Data Science Remote Internship job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $44,701 per year, or $21.5 per hour.

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Re-posted 6 days ago

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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