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

BNSF Railway

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

REMOTE Anticipated Start Date: 07/01/2026 The US base salary range for this full-time position is ... Apply data science skills to analyze large, complex datasets and identify meaningful patterns that ...

Kemper

Data Scientist

Dallas, TX · On-site +1

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Remote options are available for non-local candidate. * The range for this position is $93,300 to ...

Bread Financial

Lead Data Scientist

Frisco, TX · On-site +1

$138K - $272K/yr

The Lead Data Scientist is pivotal in generating insights and supporting the enterprise's data ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Toyota

Data Scientist

Plano, TX · On-site +1

... and remote work on Fridays Who we're looking for: Toyota Financial Services is seeking highly ... Experience working in Data Science outside of a degree-seeking academic program. What we'll bring ...

BNSF Railway

Data Scientist I/II (Remote - US)

TX · On-site +1

$93K - $175K/yr

Remote US Anticipated Start Date: 08/03/2026 The US base salary range for this full-time position ... Apply data science skills to analyze large, complex datasets and identify meaningful patterns that ...

Gartner

Data Analyst

Irving, TX · On-site +1

Projects will also involve collaboration with the Information Technology and Data Science teams ... Gartner offers a hybrid, flexible environment, with remote work that allows associates great ...

Orionyx Enginnering

Data Analyst

Dallas, TX · Remote

$23.50 - $30.50/hr

This is a remote role strictly for candidates within the United States. Position Overview: As a ... Education: * Bachelors degree in Data Science, Engineering, Statistics, Computer Science, or a ...

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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Entry Level Data Scientist Remote information

What are some common 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, difficulties in understanding team expectations, and staying motivated without in-person supervision. To overcome these, it's helpful to proactively communicate with teammates and supervisors, seek regular feedback, and participate in virtual team meetings or collaborative coding sessions. Leveraging online communities and internal chat channels can also help build connections and access guidance when needed, ensuring continued learning and integration into the team.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks like data cleaning and basic analysis, but it is unlikely to fully replace them. Data scientists are needed to interpret complex results, develop models, and make strategic decisions that require domain expertise and critical thinking. Skills in programming, statistical analysis, and machine learning remain essential for the role, especially in an evolving AI landscape.

Is 40 too late for data science?

Entry level data scientists can start at any age, including 40, as the field values skills like programming, statistics, and data analysis that can be learned at any stage. Many professionals successfully transition into data science later in their careers by gaining relevant certifications and building a portfolio of projects.

How can I make $2000 a week working from home?

An entry level data scientist working remotely can increase earnings by gaining in-demand skills like machine learning and data analysis, obtaining relevant certifications, and working on multiple freelance projects or consulting. Building a strong portfolio and leveraging platforms like Upwork or Kaggle can also help secure higher-paying opportunities. Earning $2000 weekly typically requires consistent project work and advanced skills in data tools and programming languages.

Can I get a data scientist job with no experience?

Entry level data scientist roles often require some knowledge of programming languages like Python or R, and familiarity with data analysis tools and techniques. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve chances of securing such positions. Employers may also consider internships or bootcamps as valid experience for entry level roles.

What are the key skills and qualifications needed to thrive as an Entry Level Data Scientist (Remote), and why are they important?

To thrive as an Entry Level Data Scientist (Remote), you need a solid foundation in statistics, programming (especially Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like SQL, Jupyter Notebooks, and machine learning libraries (such as scikit-learn or TensorFlow), as well as experience with data visualization platforms, is often expected. Strong problem-solving skills, self-motivation, and clear communication are crucial for collaborating across teams and working independently in a remote environment. These skills and qualities ensure you can effectively extract insights from data and contribute meaningfully to business decisions, even without direct in-person supervision.

What is an Entry Level Data Scientist (Remote)?

An Entry Level Data Scientist (Remote) is a professional who analyzes and interprets complex digital data to help companies make informed decisions, typically working from a location outside of the company's physical office. They use statistical techniques, machine learning, and data visualization tools to uncover insights from large datasets. Entry level positions are designed for individuals with limited professional experience, often recent graduates or those transitioning into the field. Remote roles offer flexibility, enabling employees to work from home or any other location with internet access.
What are popular job titles related to Entry Level Data Scientist Remote jobs in Texas? For Entry Level Data Scientist Remote jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Scientist Remote jobs in Texas look for? The top searched job categories for Entry Level Data Scientist Remote jobs in Texas are:
What cities in Texas are hiring for Entry Level Data Scientist Remote jobs? Cities in Texas with the most Entry Level Data Scientist Remote job openings:
Entry Level Data Scientist Remote jobs near you
Infographic showing various Entry Level Data Scientist Remote job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Posted 23 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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